tests/testthat/test_sampleRealizations.R
In ksauby/ACS: Adaptive Cluster Sampling
# sims=2
# n1_vec=c(5,10)
# population <- createPop(x_start = 1, x_end = 30, y_start = 1, y_end = 30)
# avar = NULL
# ovar = c(
# "Stricta",
# "Pusilla",
# "Cactus"
# )
# yvar="Cactus"
# rvar=NULL
# SamplingDesign="ACS"
# y_HT_formula = "y_HT"
# var_formula = "var_y_HT"
# m_threshold = NULL
# f_max = 2
# SampleEstimators = FALSE
# SpatStat = TRUE
# mChar = TRUE
# popvar = "n.networks"
# realvar = "realization"
# weights="S"
# seed = 1
# data(CactusRealizations)
# popdata = CactusRealizations %>%
# filter(n.networks==5 | n.networks==10 | n.networks==15 | n.networks==20)
#
# # WHY IS THERE ISLAND=NA
# simulation_data <- sampleRealizations(
# popdata=popdata,
# sims=sims,
# n1_vec=n1_vec,
# avar=avar,
# ovar=ovar,
# rvar=rvar,
# #ACS=TRUE,
# SamplingDesign=SamplingDesign,
# yvar=yvar,
# y_HT_formula=y_HT_formula,
# var_formula=var_formula,
# m_threshold=m_threshold,
# f_max=f_max,
# SampleEstimators=SampleEstimators,
# SpatStat=SpatStat,
# mChar=mChar,
# popvar=popvar,
# realvar=realvar,
# weights=weights,
# seed=seed
# )
#
# #simulation_data %<>% filter(popvar < 30)
# realvar <- 1
# yvar <- "Cactus"
# # n1=5, popvar=5 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 5
# popdata05 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_05_01 <- sim_seeds[1]
# #set.seed(seed_05_05_01)
# alldata <- createACS(popdata=popdata05, seed=seed_05_05_01, n1=n1, yvar=yvar)
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# N.ACS.plots_05_05_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_05_01 <- dim(alldata)[1]
#
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_05_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_05_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_05_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_05_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_05_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_05_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_05_01 = mean(temp$m)
# median_m_05_05_01 = median(temp$m)
# max_m_05_05_01 = max(temp$m)
# min_m_05_05_01 = min(temp$m)
# mean_uniq_m_05_05_01 = mean(unique(temp$m))
# median_uniq_m_05_05_01 = median(unique(temp$m))
# max_uniq_m_05_05_01 = max(unique(temp$m))
# min_uniq_m_05_05_01 = min(unique(temp$m))
# } else {
# mean_m_05_05_01 = NA
# median_m_05_05_01 = NA
# max_m_05_05_01 = NA
# min_m_05_05_01 = NA
# mean_uniq_m_05_05_01 = NA
# median_uniq_m_05_05_01 = NA
# max_uniq_m_05_05_01 = NA
# min_uniq_m_05_05_01 = NA
# }
#
#
# # sim 2
# seed_05_05_02 <- sim_seeds[2]
# #set.seed(seed_05_05_02)
# alldata <- createACS(popdata=popdata05, seed=seed_05_05_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_05_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_05_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_05_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_05_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_05_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_05_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_05_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_05_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_05_02 = mean(temp$m)
# median_m_05_05_02 = median(temp$m)
# max_m_05_05_02 = max(temp$m)
# min_m_05_05_02 = min(temp$m)
# mean_uniq_m_05_05_02 = mean(unique(temp$m))
# median_uniq_m_05_05_02 = median(unique(temp$m))
# max_uniq_m_05_05_02 = max(unique(temp$m))
# min_uniq_m_05_05_02 = min(unique(temp$m))
# } else {
# mean_m_05_05_02 = NA
# median_m_05_05_02 = NA
# max_m_05_05_02 = NA
# min_m_05_05_02 = NA
# mean_uniq_m_05_05_02 = NA
# median_uniq_m_05_05_02 = NA
# max_uniq_m_05_05_02 = NA
# min_uniq_m_05_05_02 = NA
# }
#
#
#
# # n1=10, popvar=5 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 5
#
# # sim 1
# seed_10_05_01 <- sim_seeds[1]
# #set.seed(seed_10_05_01)
# alldata <- createACS(popdata=popdata05, seed=seed_10_05_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_05_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_05_01 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_05_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_05_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_05_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_05_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_05_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_05_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_05_01 = mean(temp$m)
# median_m_10_05_01 = median(temp$m)
# max_m_10_05_01 = max(temp$m)
# min_m_10_05_01 = min(temp$m)
# mean_uniq_m_10_05_01 = mean(unique(temp$m))
# median_uniq_m_10_05_01 = median(unique(temp$m))
# max_uniq_m_10_05_01 = max(unique(temp$m))
# min_uniq_m_10_05_01 = min(unique(temp$m))
# } else {
# mean_m_10_05_01 = NA
# median_m_10_05_01 = NA
# max_m_10_05_01 = NA
# min_m_10_05_01 = NA
# mean_uniq_m_10_05_01 = NA
# median_uniq_m_10_05_01 = NA
# max_uniq_m_10_05_01 = NA
# min_uniq_m_10_05_01 = NA
# }
#
#
#
# # sim 2
# seed_10_05_02 <- sim_seeds[2]
# #set.seed(seed_10_05_02)
# alldata <- createACS(popdata=popdata05, seed=seed_10_05_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_05_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_05_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_05_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_05_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_05_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_05_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_05_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_05_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_05_02 = mean(temp$m)
# median_m_10_05_02 = median(temp$m)
# max_m_10_05_02 = max(temp$m)
# min_m_10_05_02 = min(temp$m)
# mean_uniq_m_10_05_02 = mean(unique(temp$m))
# median_uniq_m_10_05_02 = median(unique(temp$m))
# max_uniq_m_10_05_02 = max(unique(temp$m))
# min_uniq_m_10_05_02 = min(unique(temp$m))
# } else {
# mean_m_10_05_02 = NA
# median_m_10_05_02 = NA
# max_m_10_05_02 = NA
# min_m_10_05_02 = NA
# mean_uniq_m_10_05_02 = NA
# median_uniq_m_10_05_02 = NA
# max_uniq_m_10_05_02 = NA
# min_uniq_m_10_05_02 = NA
# }
#
#
# # n1=5, popvar=10 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 10
# popdata10 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_10_01 <- sim_seeds[1]
# #set.seed(seed_05_10_01)
# alldata <- createACS(popdata=popdata10, seed=seed_05_10_01, n1=n1, yvar=yvar)
# N.ACS.plots_05_10_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_10_01 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_10_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_10_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_10_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_10_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_10_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_10_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_10_01 = mean(temp$m)
# median_m_05_10_01 = median(temp$m)
# max_m_05_10_01 = max(temp$m)
# min_m_05_10_01 = min(temp$m)
# mean_uniq_m_05_10_01 = mean(unique(temp$m))
# median_uniq_m_05_10_01 = median(unique(temp$m))
# max_uniq_m_05_10_01 = max(unique(temp$m))
# min_uniq_m_05_10_01 = min(unique(temp$m))
# } else {
# mean_m_05_10_01 = NA
# median_m_05_10_01 = NA
# max_m_05_10_01 = NA
# min_m_05_10_01 = NA
# mean_uniq_m_05_10_01 = NA
# median_uniq_m_05_10_01 = NA
# max_uniq_m_05_10_01 = NA
# min_uniq_m_05_10_01 = NA
# }
#
#
#
# # sim 2
# seed_05_10_02 <- sim_seeds[2]
# #set.seed(seed_05_10_02)
# alldata <- createACS(popdata=popdata10, seed=seed_05_10_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_10_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_10_02 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_10_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_10_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_10_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_10_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_10_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_10_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_10_02 = mean(temp$m)
# median_m_05_10_02 = median(temp$m)
# max_m_05_10_02 = max(temp$m)
# min_m_05_10_02 = min(temp$m)
# mean_uniq_m_05_10_02 = mean(unique(temp$m))
# median_uniq_m_05_10_02 = median(unique(temp$m))
# max_uniq_m_05_10_02 = max(unique(temp$m))
# min_uniq_m_05_10_02 = min(unique(temp$m))
# } else {
# mean_m_05_10_02 = NA
# median_m_05_10_02 = NA
# max_m_05_10_02 = NA
# min_m_05_10_02 = NA
# mean_uniq_m_05_10_02 = NA
# median_uniq_m_05_10_02 = NA
# max_uniq_m_05_10_02 = NA
# min_uniq_m_05_10_02 = NA
# }
#
# # sim 2
# # n1=10, popvar=10 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 10
#
# # sim 1
# seed_10_10_01 <- sim_seeds[1]
# #set.seed(seed_10_10_01)
# alldata <- createACS(popdata=popdata10, seed=seed_10_10_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_10_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_10_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_10_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_10_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_10_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_10_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_10_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_10_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_10_01 = mean(temp$m)
# median_m_10_10_01 = median(temp$m)
# max_m_10_10_01 = max(temp$m)
# min_m_10_10_01 = min(temp$m)
# mean_uniq_m_10_10_01 = mean(unique(temp$m))
# median_uniq_m_10_10_01 = median(unique(temp$m))
# max_uniq_m_10_10_01 = max(unique(temp$m))
# min_uniq_m_10_10_01 = min(unique(temp$m))
# } else {
# mean_m_10_10_01 = NA
# median_m_10_10_01 = NA
# max_m_10_10_01 = NA
# min_m_10_10_01 = NA
# mean_uniq_m_10_10_01 = NA
# median_uniq_m_10_10_01 = NA
# max_uniq_m_10_10_01 = NA
# min_uniq_m_10_10_01 = NA
# }
#
#
# # sim 2
# seed_10_10_02 <- sim_seeds[2]
# #set.seed(seed_10_10_02)
# alldata <- createACS(popdata=popdata10, seed=seed_10_10_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_10_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_10_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_10_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_10_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_10_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_10_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_10_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_10_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_10_02 = mean(temp$m)
# median_m_10_10_02 = median(temp$m)
# max_m_10_10_02 = max(temp$m)
# min_m_10_10_02 = min(temp$m)
# mean_uniq_m_10_10_02 = mean(unique(temp$m))
# median_uniq_m_10_10_02 = median(unique(temp$m))
# max_uniq_m_10_10_02 = max(unique(temp$m))
# min_uniq_m_10_10_02 = min(unique(temp$m))
# } else {
# mean_m_10_10_02 = NA
# median_m_10_10_02 = NA
# max_m_10_10_02 = NA
# min_m_10_10_02 = NA
# mean_uniq_m_10_10_02 = NA
# median_uniq_m_10_10_02 = NA
# max_uniq_m_10_10_02 = NA
# min_uniq_m_10_10_02 = NA
# }
#
#
# # n1=5, popvar=15 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 15
# popdata15 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_15_01 <- sim_seeds[1]
# #set.seed(seed_05_15_01)
# alldata <- createACS(popdata=popdata15, seed=seed_05_15_01, n1=n1, yvar=yvar)
# N.ACS.plots_05_15_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_15_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_15_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_15_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_15_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_15_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_15_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_15_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_15_01 = mean(temp$m)
# median_m_05_15_01 = median(temp$m)
# max_m_05_15_01 = max(temp$m)
# min_m_05_15_01 = min(temp$m)
# mean_uniq_m_05_15_01 = mean(unique(temp$m))
# median_uniq_m_05_15_01 = median(unique(temp$m))
# max_uniq_m_05_15_01 = max(unique(temp$m))
# min_uniq_m_05_15_01 = min(unique(temp$m))
# } else {
# mean_m_05_15_01 = NA
# median_m_05_15_01 = NA
# max_m_05_15_01 = NA
# min_m_05_15_01 = NA
# mean_uniq_m_05_15_01 = NA
# median_uniq_m_05_15_01 = NA
# max_uniq_m_05_15_01 = NA
# min_uniq_m_05_15_01 = NA
# }
#
#
# # sim 2
# seed_05_15_02 <- sim_seeds[2]
# #set.seed(seed_05_15_02)
# alldata <- createACS(popdata=popdata15, seed=seed_05_15_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_15_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_15_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_15_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_15_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_15_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_15_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_15_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_15_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_15_02 = mean(temp$m)
# median_m_05_15_02 = median(temp$m)
# max_m_05_15_02 = max(temp$m)
# min_m_05_15_02 = min(temp$m)
# mean_uniq_m_05_15_02 = mean(unique(temp$m))
# median_uniq_m_05_15_02 = median(unique(temp$m))
# max_uniq_m_05_15_02 = max(unique(temp$m))
# min_uniq_m_05_15_02 = min(unique(temp$m))
# } else {
# mean_m_05_15_02 = NA
# median_m_05_15_02 = NA
# max_m_05_15_02 = NA
# min_m_05_15_02 = NA
# mean_uniq_m_05_15_02 = NA
# median_uniq_m_05_15_02 = NA
# max_uniq_m_05_15_02 = NA
# min_uniq_m_05_15_02 = NA
# }
#
# # n1=10, popvar=15 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 15
#
# # sim 1
# seed_10_15_01 <- sim_seeds[1]
# #set.seed(seed_10_15_01)
# alldata <- createACS(popdata=popdata15, seed=seed_10_15_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_15_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_15_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_15_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_15_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_15_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_15_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_15_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_15_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_15_01 = mean(temp$m)
# median_m_10_15_01 = median(temp$m)
# max_m_10_15_01 = max(temp$m)
# min_m_10_15_01 = min(temp$m)
# mean_uniq_m_10_15_01 = mean(unique(temp$m))
# median_uniq_m_10_15_01 = median(unique(temp$m))
# max_uniq_m_10_15_01 = max(unique(temp$m))
# min_uniq_m_10_15_01 = min(unique(temp$m))
# } else {
# mean_m_10_15_01 = NA
# median_m_10_15_01 = NA
# max_m_10_15_01 = NA
# min_m_10_15_01 = NA
# mean_uniq_m_10_15_01 = NA
# median_uniq_m_10_15_01 = NA
# max_uniq_m_10_15_01 = NA
# min_uniq_m_10_15_01 = NA
# }
#
#
#
# # sim 2
# seed_10_15_02 <- sim_seeds[2]
# #set.seed(seed_10_15_02)
# alldata <- createACS(popdata=popdata15, seed=seed_10_15_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_15_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_15_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_15_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_15_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_15_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_15_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_15_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_15_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_15_02 = mean(temp$m)
# median_m_10_15_02 = median(temp$m)
# max_m_10_15_02 = max(temp$m)
# min_m_10_15_02 = min(temp$m)
# mean_uniq_m_10_15_02 = mean(unique(temp$m))
# median_uniq_m_10_15_02 = median(unique(temp$m))
# max_uniq_m_10_15_02 = max(unique(temp$m))
# min_uniq_m_10_15_02 = min(unique(temp$m))
# } else {
# mean_m_10_15_02 = NA
# median_m_10_15_02 = NA
# max_m_10_15_02 = NA
# min_m_10_15_02 = NA
# mean_uniq_m_10_15_02 = NA
# median_uniq_m_10_15_02 = NA
# max_uniq_m_10_15_02 = NA
# min_uniq_m_10_15_02 = NA
# }
#
# # n1=5, popvar=20 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 20
# popdata20 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_20_01 <- sim_seeds[1]
# #set.seed(seed_05_20_01)
# alldata <- createACS(popdata=popdata20, seed=seed_05_20_01, n1=n1, yvar=yvar)
# N.ACS.plots_05_20_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_20_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_20_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_20_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_20_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_20_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_20_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_20_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_20_01 = mean(temp$m)
# median_m_05_20_01 = median(temp$m)
# max_m_05_20_01 = max(temp$m)
# min_m_05_20_01 = min(temp$m)
# mean_uniq_m_05_20_01 = mean(unique(temp$m))
# median_uniq_m_05_20_01 = median(unique(temp$m))
# max_uniq_m_05_20_01 = max(unique(temp$m))
# min_uniq_m_05_20_01 = min(unique(temp$m))
# } else {
# mean_m_05_20_01 = NA
# median_m_05_20_01 = NA
# max_m_05_20_01 = NA
# min_m_05_20_01 = NA
# mean_uniq_m_05_20_01 = NA
# median_uniq_m_05_20_01 = NA
# max_uniq_m_05_20_01 = NA
# min_uniq_m_05_20_01 = NA
# }
#
#
#
# # sim 2
# seed_05_20_02 <- sim_seeds[2]
# #set.seed(seed_05_20_02)
# alldata <- createACS(popdata=popdata20, seed=seed_05_20_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_20_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_20_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_20_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_20_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_20_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_20_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_20_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_20_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_20_02 = mean(temp$m)
# median_m_05_20_02 = median(temp$m)
# max_m_05_20_02 = max(temp$m)
# min_m_05_20_02 = min(temp$m)
# mean_uniq_m_05_20_02 = mean(unique(temp$m))
# median_uniq_m_05_20_02 = median(unique(temp$m))
# max_uniq_m_05_20_02 = max(unique(temp$m))
# min_uniq_m_05_20_02 = min(unique(temp$m))
# } else {
# mean_m_05_20_02 = NA
# median_m_05_20_02 = NA
# max_m_05_20_02 = NA
# min_m_05_20_02 = NA
# mean_uniq_m_05_20_02 = NA
# median_uniq_m_05_20_02 = NA
# max_uniq_m_05_20_02 = NA
# min_uniq_m_05_20_02 = NA
# }
#
# # n1=10, popvar=20 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 20
#
# # sim 1
# seed_10_20_01 <- sim_seeds[1]
# #set.seed(seed_10_20_01)
# alldata <- createACS(popdata=popdata20, seed=seed_10_20_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_20_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_20_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_20_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_20_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_20_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_20_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_20_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_20_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_20_01 = mean(temp$m)
# median_m_10_20_01 = median(temp$m)
# max_m_10_20_01 = max(temp$m)
# min_m_10_20_01 = min(temp$m)
# mean_uniq_m_10_20_01 = mean(unique(temp$m))
# median_uniq_m_10_20_01 = median(unique(temp$m))
# max_uniq_m_10_20_01 = max(unique(temp$m))
# min_uniq_m_10_20_01 = min(unique(temp$m))
# } else {
# mean_m_10_20_01 = NA
# median_m_10_20_01 = NA
# max_m_10_20_01 = NA
# min_m_10_20_01 = NA
# mean_uniq_m_10_20_01 = NA
# median_uniq_m_10_20_01 = NA
# max_uniq_m_10_20_01 = NA
# min_uniq_m_10_20_01 = NA
# }
#
#
#
# # sim 2
# seed_10_20_02 <- sim_seeds[2]
# #set.seed(seed_10_20_02)
# alldata <- createACS(popdata=popdata20, seed=seed_10_20_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_20_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_20_02 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_20_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_20_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_20_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_20_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_20_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_20_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_20_02 = mean(temp$m)
# median_m_10_20_02 = median(temp$m)
# max_m_10_20_02 = max(temp$m)
# min_m_10_20_02 = min(temp$m)
# mean_uniq_m_10_20_02 = mean(unique(temp$m))
# median_uniq_m_10_20_02 = median(unique(temp$m))
# max_uniq_m_10_20_02 = max(unique(temp$m))
# min_uniq_m_10_20_02 = min(unique(temp$m))
# } else {
# mean_m_10_20_02 = NA
# median_m_10_20_02 = NA
# max_m_10_20_02 = NA
# min_m_10_20_02 = NA
# mean_uniq_m_10_20_02 = NA
# median_uniq_m_10_20_02 = NA
# max_uniq_m_10_20_02 = NA
# min_uniq_m_10_20_02 = NA
# }
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
# seed <- c(
# seed_05_05_01, seed_05_05_02,
# seed_10_05_01, seed_10_05_02,
#
# seed_05_10_01, seed_05_10_02,
# seed_10_10_01, seed_10_10_02,
#
# seed_05_15_01, seed_05_15_02,
# seed_10_15_01, seed_10_15_02,
#
# seed_05_20_01, seed_05_20_02,
# seed_10_20_01, seed_10_20_02
# )
#
# Stricta_yHT <- c(
# Stricta_yHT_05_05_01, Stricta_yHT_05_05_02,
# Stricta_yHT_10_05_01, Stricta_yHT_10_05_02,
#
# Stricta_yHT_05_10_01, Stricta_yHT_05_10_02,
# Stricta_yHT_10_10_01, Stricta_yHT_10_10_02,
#
# Stricta_yHT_05_15_01, Stricta_yHT_05_15_02,
# Stricta_yHT_10_15_01, Stricta_yHT_10_15_02,
#
# Stricta_yHT_05_20_01, Stricta_yHT_05_20_02,
# Stricta_yHT_10_20_01, Stricta_yHT_10_20_02
# )
#
# Pusilla_yHT <- c(
# Pusilla_yHT_05_05_01, Pusilla_yHT_05_05_02,
# Pusilla_yHT_10_05_01, Pusilla_yHT_10_05_02,
#
# Pusilla_yHT_05_10_01, Pusilla_yHT_05_05_02,
# Pusilla_yHT_10_10_01, Pusilla_yHT_10_05_02,
#
# Pusilla_yHT_05_15_01, Pusilla_yHT_05_15_02,
# Pusilla_yHT_10_15_01, Pusilla_yHT_10_15_02,
#
# Pusilla_yHT_05_20_01, Pusilla_yHT_05_20_02,
# Pusilla_yHT_10_20_01, Pusilla_yHT_10_20_02
# )
#
# Cactus_yHT <- c(
# Cactus_yHT_05_05_01, Cactus_yHT_05_05_02,
# Cactus_yHT_10_05_01, Cactus_yHT_10_05_02,
#
# Cactus_yHT_05_10_01, Cactus_yHT_05_10_02,
# Cactus_yHT_10_10_01, Cactus_yHT_10_10_02,
#
# Cactus_yHT_05_15_01, Cactus_yHT_05_15_02,
# Cactus_yHT_10_15_01, Cactus_yHT_10_15_02,
#
# Cactus_yHT_05_20_01, Cactus_yHT_05_20_02,
# Cactus_yHT_10_20_01, Cactus_yHT_10_20_02
# )
#
# Stricta_var_yHT <- c(
# Stricta_var_yHT_05_05_01, Stricta_var_yHT_05_05_02,
# Stricta_var_yHT_10_05_01, Stricta_var_yHT_10_05_02,
#
# Stricta_var_yHT_05_10_01, Stricta_var_yHT_05_10_02,
# Stricta_var_yHT_10_10_01, Stricta_var_yHT_10_10_02,
#
# Stricta_var_yHT_05_15_01, Stricta_var_yHT_05_15_02,
# Stricta_var_yHT_10_15_01, Stricta_var_yHT_10_15_02,
#
# Stricta_var_yHT_05_20_01, Stricta_var_yHT_05_20_02,
# Stricta_var_yHT_10_20_01, Stricta_var_yHT_10_20_02
# )
#
#
# Pusilla_var_yHT <- c(
# Pusilla_var_yHT_05_05_01, Pusilla_var_yHT_05_05_02,
# Pusilla_var_yHT_10_05_01, Pusilla_var_yHT_10_05_02,
#
# Pusilla_var_yHT_05_10_01, Pusilla_var_yHT_05_10_02,
# Pusilla_var_yHT_10_10_01, Pusilla_var_yHT_10_10_02,
#
# Pusilla_var_yHT_05_15_01, Pusilla_var_yHT_05_15_02,
# Pusilla_var_yHT_10_15_01, Pusilla_var_yHT_10_15_02,
#
# Pusilla_var_yHT_05_20_01, Pusilla_var_yHT_05_20_02,
# Pusilla_var_yHT_10_20_01, Pusilla_var_yHT_10_20_02
# )
#
# Cactus_var_yHT <- c(
# Cactus_var_yHT_05_05_01, Cactus_var_yHT_05_05_02,
# Cactus_var_yHT_10_05_01, Cactus_var_yHT_10_05_02,
#
# Cactus_var_yHT_05_10_01, Cactus_var_yHT_05_10_02,
# Cactus_var_yHT_10_10_01, Cactus_var_yHT_10_10_02,
#
# Cactus_var_yHT_05_15_01, Cactus_var_yHT_05_15_02,
# Cactus_var_yHT_10_15_01, Cactus_var_yHT_10_15_02,
#
# Cactus_var_yHT_05_20_01, Cactus_var_yHT_05_20_02,
# Cactus_var_yHT_10_20_01, Cactus_var_yHT_10_20_02
# )
#
# mean_m <- c(
# mean_m_05_05_01, mean_m_05_05_02,
# mean_m_10_05_01, mean_m_10_05_02,
#
# mean_m_05_10_01, mean_m_05_10_02,
# mean_m_10_10_01, mean_m_10_10_02,
#
# mean_m_05_15_01, mean_m_05_15_02,
# mean_m_10_15_01, mean_m_10_15_02,
#
# mean_m_05_20_01, mean_m_05_20_02,
# mean_m_10_20_01, mean_m_10_20_02
# )
#
# median_m <- c(
# median_m_05_05_01, median_m_05_05_02,
# median_m_10_05_01, median_m_10_05_02,
#
# median_m_05_10_01, median_m_05_10_02,
# median_m_10_10_01, median_m_10_10_02,
#
# median_m_05_15_01, median_m_05_15_02,
# median_m_10_15_01, median_m_10_15_02,
#
# median_m_05_20_01, median_m_05_20_02,
# median_m_10_20_01, median_m_10_20_02
# )
#
# max_m <- c(
# max_m_05_05_01, max_m_05_05_02,
# max_m_10_05_01, max_m_10_05_02,
#
# max_m_05_10_01, max_m_05_10_02,
# max_m_10_10_01, max_m_10_10_02,
#
# max_m_05_15_01, max_m_05_15_02,
# max_m_10_15_01, max_m_10_15_02,
#
# max_m_05_20_01, max_m_05_20_02,
# max_m_10_20_01, max_m_10_20_02
# )
#
# min_m <- c(
# min_m_05_05_01, min_m_05_05_02,
# min_m_10_05_01, min_m_10_05_02,
#
# min_m_05_10_01, min_m_05_10_02,
# min_m_10_10_01, min_m_10_10_02,
#
# min_m_05_15_01, min_m_05_15_02,
# min_m_10_15_01, min_m_10_15_02,
#
# min_m_05_20_01, min_m_05_20_02,
# min_m_10_20_01, min_m_10_20_02
# )
#
# mean_uniq_m <- c(
# mean_uniq_m_05_05_01, mean_uniq_m_05_05_02,
# mean_uniq_m_10_05_01, mean_uniq_m_10_05_02,
#
# mean_uniq_m_05_10_01, mean_uniq_m_05_10_02,
# mean_uniq_m_10_10_01, mean_uniq_m_10_10_02,
#
# mean_uniq_m_05_15_01, mean_uniq_m_05_15_02,
# mean_uniq_m_10_15_01, mean_uniq_m_10_15_02,
#
# mean_uniq_m_05_20_01, mean_uniq_m_05_20_02,
# mean_uniq_m_10_20_01, mean_uniq_m_10_20_02
# )
#
# median_uniq_m <- c(
# median_uniq_m_05_05_01, median_uniq_m_05_05_02,
# median_uniq_m_10_05_01, median_uniq_m_10_05_02,
#
# median_uniq_m_05_10_01, median_uniq_m_05_10_02,
# median_uniq_m_10_10_01, median_uniq_m_10_10_02,
#
# median_uniq_m_05_15_01, median_uniq_m_05_15_02,
# median_uniq_m_10_15_01, median_uniq_m_10_15_02,
#
# median_uniq_m_05_20_01, median_uniq_m_05_20_02,
# median_uniq_m_10_20_01, median_uniq_m_10_20_02
# )
#
# max_uniq_m <- c(
# max_uniq_m_05_05_01, max_uniq_m_05_05_02,
# max_uniq_m_10_05_01, max_uniq_m_10_05_02,
#
# max_uniq_m_05_10_01, max_uniq_m_05_10_02,
# max_uniq_m_10_10_01, max_uniq_m_10_10_02,
#
# max_uniq_m_05_15_01, max_uniq_m_05_15_02,
# max_uniq_m_10_15_01, max_uniq_m_10_15_02,
#
# max_uniq_m_05_20_01, max_uniq_m_05_20_02,
# max_uniq_m_10_20_01, max_uniq_m_10_20_02
# )
#
# min_uniq_m <- c(
# min_uniq_m_05_05_01, min_uniq_m_05_05_02,
# min_uniq_m_10_05_01, min_uniq_m_10_05_02,
#
# min_uniq_m_05_10_01, min_uniq_m_05_10_02,
# min_uniq_m_10_10_01, min_uniq_m_10_10_02,
#
# min_uniq_m_05_15_01, min_uniq_m_05_15_02,
# min_uniq_m_10_15_01, min_uniq_m_10_15_02,
#
# min_uniq_m_05_20_01, min_uniq_m_05_20_02,
# min_uniq_m_10_20_01, min_uniq_m_10_20_02
# )
#
# N.ACS.plots <- c(
# N.ACS.plots_05_05_01, N.ACS.plots_05_05_02,
# N.ACS.plots_10_05_01, N.ACS.plots_10_05_02,
#
# N.ACS.plots_05_10_01, N.ACS.plots_05_10_02,
# N.ACS.plots_10_10_01, N.ACS.plots_10_10_02,
#
# N.ACS.plots_05_15_01, N.ACS.plots_05_15_02,
# N.ACS.plots_10_15_01, N.ACS.plots_10_15_02,
#
# N.ACS.plots_05_20_01, N.ACS.plots_05_20_02,
# N.ACS.plots_10_20_01, N.ACS.plots_10_20_02
# )
#
# N.Total.plots <- c(
# N.Total.plots_05_05_01, N.Total.plots_05_05_02,
# N.Total.plots_10_05_01, N.Total.plots_10_05_02,
#
# N.Total.plots_05_10_01, N.Total.plots_05_10_02,
# N.Total.plots_10_10_01, N.Total.plots_10_10_02,
#
# N.Total.plots_05_15_01, N.Total.plots_05_15_02,
# N.Total.plots_10_15_01, N.Total.plots_10_15_02,
#
# N.Total.plots_05_20_01, N.Total.plots_05_20_02,
# N.Total.plots_10_20_01, N.Total.plots_10_20_02
# )
#
#
# simulation_data %<>%
# dplyr::select(
# -c(JoinCountTest.S, MoranI.S, SimDate)
# )
#
# # simulation_data %<>%
# # dplyr::select(
# # -c(mean_m,
# # median_m,
# # max_m,
# # min_m,
# # mean_uniq_m,
# # median_uniq_m,
# # max_uniq_m,
# # min_uniq_m
# # #JoinCountTest.S,
# # )
# # )
#
#
# manually_calculated <- data.frame(
# Stricta_yHT,
# Pusilla_yHT,
# Cactus_yHT,
# Stricta_var_yHT,
# Pusilla_var_yHT,
# Cactus_var_yHT,
# Plots = "Horvitz Thompson Mean (All Plots)",
# simulation = rep(1:2, 2),
# seed,
# N.ACS.plots,
# N.Total.plots,
# realvar = 1,
# popvar = c(rep(5,4), rep(10, 4), rep(15, 4), rep(20, 4)),
# N.SRSWOR.plots = rep(c(rep(5, 2), rep(10, 2)), 4),
# mean_m,
# median_m,
# max_m,
# min_m,
# mean_uniq_m,
# median_uniq_m,
# max_uniq_m,
# min_uniq_m,
# #JoinCountTest.S,
# #MoranI.S,
# f_max = 2,
# nSims = 2,
# y_HT_formula = "y_HT",
# SamplingDesign = "ACS",
# MoransIWeightMatrix = weights
# )
#
#
# test_that("test sampleRealizations", {
# expect_equal(
# simulation_data,
# manually_calculated
# )
# })
#
# popvar = "n.networks"
# realvar = "realization"
#
# simulation_data_sample_estimators <- sampleRealizations(
# popdata=popdata,
# sims=sims,
# n1_vec=n1_vec,
# avar=avar,
# ovar=ovar,
# rvar=rvar,
# #ACS=TRUE,
# SamplingDesign=SamplingDesign,
# yvar=yvar,
# y_HT_formula=y_HT_formula,
# var_formula=var_formula,
# m_threshold=m_threshold,
# f_max=f_max,
# SampleEstimators=TRUE,
# SpatStat=SpatStat,
# mChar=mChar,
# popvar=popvar,
# realvar=realvar,
# weights=weights,
# seed=seed
# )
ksauby/ACS documentation built on Aug. 18, 2022, 3:33 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# sims=2
# n1_vec=c(5,10)
# population <- createPop(x_start = 1, x_end = 30, y_start = 1, y_end = 30)
# avar = NULL
# ovar = c(
# "Stricta",
# "Pusilla",
# "Cactus"
# )
# yvar="Cactus"
# rvar=NULL
# SamplingDesign="ACS"
# y_HT_formula = "y_HT"
# var_formula = "var_y_HT"
# m_threshold = NULL
# f_max = 2
# SampleEstimators = FALSE
# SpatStat = TRUE
# mChar = TRUE
# popvar = "n.networks"
# realvar = "realization"
# weights="S"
# seed = 1
# data(CactusRealizations)
# popdata = CactusRealizations %>%
# filter(n.networks==5 | n.networks==10 | n.networks==15 | n.networks==20)
#
# # WHY IS THERE ISLAND=NA
# simulation_data <- sampleRealizations(
# popdata=popdata,
# sims=sims,
# n1_vec=n1_vec,
# avar=avar,
# ovar=ovar,
# rvar=rvar,
# #ACS=TRUE,
# SamplingDesign=SamplingDesign,
# yvar=yvar,
# y_HT_formula=y_HT_formula,
# var_formula=var_formula,
# m_threshold=m_threshold,
# f_max=f_max,
# SampleEstimators=SampleEstimators,
# SpatStat=SpatStat,
# mChar=mChar,
# popvar=popvar,
# realvar=realvar,
# weights=weights,
# seed=seed
# )
#
# #simulation_data %<>% filter(popvar < 30)
# realvar <- 1
# yvar <- "Cactus"
# # n1=5, popvar=5 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 5
# popdata05 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_05_01 <- sim_seeds[1]
# #set.seed(seed_05_05_01)
# alldata <- createACS(popdata=popdata05, seed=seed_05_05_01, n1=n1, yvar=yvar)
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# N.ACS.plots_05_05_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_05_01 <- dim(alldata)[1]
#
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_05_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_05_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_05_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_05_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_05_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_05_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_05_01 = mean(temp$m)
# median_m_05_05_01 = median(temp$m)
# max_m_05_05_01 = max(temp$m)
# min_m_05_05_01 = min(temp$m)
# mean_uniq_m_05_05_01 = mean(unique(temp$m))
# median_uniq_m_05_05_01 = median(unique(temp$m))
# max_uniq_m_05_05_01 = max(unique(temp$m))
# min_uniq_m_05_05_01 = min(unique(temp$m))
# } else {
# mean_m_05_05_01 = NA
# median_m_05_05_01 = NA
# max_m_05_05_01 = NA
# min_m_05_05_01 = NA
# mean_uniq_m_05_05_01 = NA
# median_uniq_m_05_05_01 = NA
# max_uniq_m_05_05_01 = NA
# min_uniq_m_05_05_01 = NA
# }
#
#
# # sim 2
# seed_05_05_02 <- sim_seeds[2]
# #set.seed(seed_05_05_02)
# alldata <- createACS(popdata=popdata05, seed=seed_05_05_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_05_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_05_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_05_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_05_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_05_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_05_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_05_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_05_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_05_02 = mean(temp$m)
# median_m_05_05_02 = median(temp$m)
# max_m_05_05_02 = max(temp$m)
# min_m_05_05_02 = min(temp$m)
# mean_uniq_m_05_05_02 = mean(unique(temp$m))
# median_uniq_m_05_05_02 = median(unique(temp$m))
# max_uniq_m_05_05_02 = max(unique(temp$m))
# min_uniq_m_05_05_02 = min(unique(temp$m))
# } else {
# mean_m_05_05_02 = NA
# median_m_05_05_02 = NA
# max_m_05_05_02 = NA
# min_m_05_05_02 = NA
# mean_uniq_m_05_05_02 = NA
# median_uniq_m_05_05_02 = NA
# max_uniq_m_05_05_02 = NA
# min_uniq_m_05_05_02 = NA
# }
#
#
#
# # n1=10, popvar=5 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 5
#
# # sim 1
# seed_10_05_01 <- sim_seeds[1]
# #set.seed(seed_10_05_01)
# alldata <- createACS(popdata=popdata05, seed=seed_10_05_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_05_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_05_01 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_05_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_05_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_05_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_05_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_05_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_05_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_05_01 = mean(temp$m)
# median_m_10_05_01 = median(temp$m)
# max_m_10_05_01 = max(temp$m)
# min_m_10_05_01 = min(temp$m)
# mean_uniq_m_10_05_01 = mean(unique(temp$m))
# median_uniq_m_10_05_01 = median(unique(temp$m))
# max_uniq_m_10_05_01 = max(unique(temp$m))
# min_uniq_m_10_05_01 = min(unique(temp$m))
# } else {
# mean_m_10_05_01 = NA
# median_m_10_05_01 = NA
# max_m_10_05_01 = NA
# min_m_10_05_01 = NA
# mean_uniq_m_10_05_01 = NA
# median_uniq_m_10_05_01 = NA
# max_uniq_m_10_05_01 = NA
# min_uniq_m_10_05_01 = NA
# }
#
#
#
# # sim 2
# seed_10_05_02 <- sim_seeds[2]
# #set.seed(seed_10_05_02)
# alldata <- createACS(popdata=popdata05, seed=seed_10_05_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_05_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_05_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_05_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_05_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_05_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_05_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_05_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_05_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_05_02 = mean(temp$m)
# median_m_10_05_02 = median(temp$m)
# max_m_10_05_02 = max(temp$m)
# min_m_10_05_02 = min(temp$m)
# mean_uniq_m_10_05_02 = mean(unique(temp$m))
# median_uniq_m_10_05_02 = median(unique(temp$m))
# max_uniq_m_10_05_02 = max(unique(temp$m))
# min_uniq_m_10_05_02 = min(unique(temp$m))
# } else {
# mean_m_10_05_02 = NA
# median_m_10_05_02 = NA
# max_m_10_05_02 = NA
# min_m_10_05_02 = NA
# mean_uniq_m_10_05_02 = NA
# median_uniq_m_10_05_02 = NA
# max_uniq_m_10_05_02 = NA
# min_uniq_m_10_05_02 = NA
# }
#
#
# # n1=5, popvar=10 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 10
# popdata10 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_10_01 <- sim_seeds[1]
# #set.seed(seed_05_10_01)
# alldata <- createACS(popdata=popdata10, seed=seed_05_10_01, n1=n1, yvar=yvar)
# N.ACS.plots_05_10_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_10_01 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_10_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_10_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_10_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_10_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_10_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_10_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_10_01 = mean(temp$m)
# median_m_05_10_01 = median(temp$m)
# max_m_05_10_01 = max(temp$m)
# min_m_05_10_01 = min(temp$m)
# mean_uniq_m_05_10_01 = mean(unique(temp$m))
# median_uniq_m_05_10_01 = median(unique(temp$m))
# max_uniq_m_05_10_01 = max(unique(temp$m))
# min_uniq_m_05_10_01 = min(unique(temp$m))
# } else {
# mean_m_05_10_01 = NA
# median_m_05_10_01 = NA
# max_m_05_10_01 = NA
# min_m_05_10_01 = NA
# mean_uniq_m_05_10_01 = NA
# median_uniq_m_05_10_01 = NA
# max_uniq_m_05_10_01 = NA
# min_uniq_m_05_10_01 = NA
# }
#
#
#
# # sim 2
# seed_05_10_02 <- sim_seeds[2]
# #set.seed(seed_05_10_02)
# alldata <- createACS(popdata=popdata10, seed=seed_05_10_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_10_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_10_02 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_10_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_10_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_10_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_10_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_10_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_10_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_10_02 = mean(temp$m)
# median_m_05_10_02 = median(temp$m)
# max_m_05_10_02 = max(temp$m)
# min_m_05_10_02 = min(temp$m)
# mean_uniq_m_05_10_02 = mean(unique(temp$m))
# median_uniq_m_05_10_02 = median(unique(temp$m))
# max_uniq_m_05_10_02 = max(unique(temp$m))
# min_uniq_m_05_10_02 = min(unique(temp$m))
# } else {
# mean_m_05_10_02 = NA
# median_m_05_10_02 = NA
# max_m_05_10_02 = NA
# min_m_05_10_02 = NA
# mean_uniq_m_05_10_02 = NA
# median_uniq_m_05_10_02 = NA
# max_uniq_m_05_10_02 = NA
# min_uniq_m_05_10_02 = NA
# }
#
# # sim 2
# # n1=10, popvar=10 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 10
#
# # sim 1
# seed_10_10_01 <- sim_seeds[1]
# #set.seed(seed_10_10_01)
# alldata <- createACS(popdata=popdata10, seed=seed_10_10_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_10_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_10_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_10_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_10_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_10_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_10_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_10_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_10_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_10_01 = mean(temp$m)
# median_m_10_10_01 = median(temp$m)
# max_m_10_10_01 = max(temp$m)
# min_m_10_10_01 = min(temp$m)
# mean_uniq_m_10_10_01 = mean(unique(temp$m))
# median_uniq_m_10_10_01 = median(unique(temp$m))
# max_uniq_m_10_10_01 = max(unique(temp$m))
# min_uniq_m_10_10_01 = min(unique(temp$m))
# } else {
# mean_m_10_10_01 = NA
# median_m_10_10_01 = NA
# max_m_10_10_01 = NA
# min_m_10_10_01 = NA
# mean_uniq_m_10_10_01 = NA
# median_uniq_m_10_10_01 = NA
# max_uniq_m_10_10_01 = NA
# min_uniq_m_10_10_01 = NA
# }
#
#
# # sim 2
# seed_10_10_02 <- sim_seeds[2]
# #set.seed(seed_10_10_02)
# alldata <- createACS(popdata=popdata10, seed=seed_10_10_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_10_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_10_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_10_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_10_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_10_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_10_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_10_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_10_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_10_02 = mean(temp$m)
# median_m_10_10_02 = median(temp$m)
# max_m_10_10_02 = max(temp$m)
# min_m_10_10_02 = min(temp$m)
# mean_uniq_m_10_10_02 = mean(unique(temp$m))
# median_uniq_m_10_10_02 = median(unique(temp$m))
# max_uniq_m_10_10_02 = max(unique(temp$m))
# min_uniq_m_10_10_02 = min(unique(temp$m))
# } else {
# mean_m_10_10_02 = NA
# median_m_10_10_02 = NA
# max_m_10_10_02 = NA
# min_m_10_10_02 = NA
# mean_uniq_m_10_10_02 = NA
# median_uniq_m_10_10_02 = NA
# max_uniq_m_10_10_02 = NA
# min_uniq_m_10_10_02 = NA
# }
#
#
# # n1=5, popvar=15 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 15
# popdata15 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_15_01 <- sim_seeds[1]
# #set.seed(seed_05_15_01)
# alldata <- createACS(popdata=popdata15, seed=seed_05_15_01, n1=n1, yvar=yvar)
# N.ACS.plots_05_15_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_15_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_15_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_15_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_15_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_15_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_15_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_15_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_15_01 = mean(temp$m)
# median_m_05_15_01 = median(temp$m)
# max_m_05_15_01 = max(temp$m)
# min_m_05_15_01 = min(temp$m)
# mean_uniq_m_05_15_01 = mean(unique(temp$m))
# median_uniq_m_05_15_01 = median(unique(temp$m))
# max_uniq_m_05_15_01 = max(unique(temp$m))
# min_uniq_m_05_15_01 = min(unique(temp$m))
# } else {
# mean_m_05_15_01 = NA
# median_m_05_15_01 = NA
# max_m_05_15_01 = NA
# min_m_05_15_01 = NA
# mean_uniq_m_05_15_01 = NA
# median_uniq_m_05_15_01 = NA
# max_uniq_m_05_15_01 = NA
# min_uniq_m_05_15_01 = NA
# }
#
#
# # sim 2
# seed_05_15_02 <- sim_seeds[2]
# #set.seed(seed_05_15_02)
# alldata <- createACS(popdata=popdata15, seed=seed_05_15_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_15_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_15_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_15_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_15_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_15_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_15_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_15_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_15_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_15_02 = mean(temp$m)
# median_m_05_15_02 = median(temp$m)
# max_m_05_15_02 = max(temp$m)
# min_m_05_15_02 = min(temp$m)
# mean_uniq_m_05_15_02 = mean(unique(temp$m))
# median_uniq_m_05_15_02 = median(unique(temp$m))
# max_uniq_m_05_15_02 = max(unique(temp$m))
# min_uniq_m_05_15_02 = min(unique(temp$m))
# } else {
# mean_m_05_15_02 = NA
# median_m_05_15_02 = NA
# max_m_05_15_02 = NA
# min_m_05_15_02 = NA
# mean_uniq_m_05_15_02 = NA
# median_uniq_m_05_15_02 = NA
# max_uniq_m_05_15_02 = NA
# min_uniq_m_05_15_02 = NA
# }
#
# # n1=10, popvar=15 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 15
#
# # sim 1
# seed_10_15_01 <- sim_seeds[1]
# #set.seed(seed_10_15_01)
# alldata <- createACS(popdata=popdata15, seed=seed_10_15_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_15_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_15_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_15_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_15_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_15_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_15_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_15_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_15_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_15_01 = mean(temp$m)
# median_m_10_15_01 = median(temp$m)
# max_m_10_15_01 = max(temp$m)
# min_m_10_15_01 = min(temp$m)
# mean_uniq_m_10_15_01 = mean(unique(temp$m))
# median_uniq_m_10_15_01 = median(unique(temp$m))
# max_uniq_m_10_15_01 = max(unique(temp$m))
# min_uniq_m_10_15_01 = min(unique(temp$m))
# } else {
# mean_m_10_15_01 = NA
# median_m_10_15_01 = NA
# max_m_10_15_01 = NA
# min_m_10_15_01 = NA
# mean_uniq_m_10_15_01 = NA
# median_uniq_m_10_15_01 = NA
# max_uniq_m_10_15_01 = NA
# min_uniq_m_10_15_01 = NA
# }
#
#
#
# # sim 2
# seed_10_15_02 <- sim_seeds[2]
# #set.seed(seed_10_15_02)
# alldata <- createACS(popdata=popdata15, seed=seed_10_15_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_15_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_15_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_15_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_15_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_15_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_15_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_15_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_15_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_15_02 = mean(temp$m)
# median_m_10_15_02 = median(temp$m)
# max_m_10_15_02 = max(temp$m)
# min_m_10_15_02 = min(temp$m)
# mean_uniq_m_10_15_02 = mean(unique(temp$m))
# median_uniq_m_10_15_02 = median(unique(temp$m))
# max_uniq_m_10_15_02 = max(unique(temp$m))
# min_uniq_m_10_15_02 = min(unique(temp$m))
# } else {
# mean_m_10_15_02 = NA
# median_m_10_15_02 = NA
# max_m_10_15_02 = NA
# min_m_10_15_02 = NA
# mean_uniq_m_10_15_02 = NA
# median_uniq_m_10_15_02 = NA
# max_uniq_m_10_15_02 = NA
# min_uniq_m_10_15_02 = NA
# }
#
# # n1=5, popvar=20 --------------------------------------------------------------#
# tseed1 <- 1
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 5
# popvar <- 20
# popdata20 <- popdata %>% filter(n.networks == popvar)
#
# # sim 1
# seed_05_20_01 <- sim_seeds[1]
# #set.seed(seed_05_20_01)
# alldata <- createACS(popdata=popdata20, seed=seed_05_20_01, n1=n1, yvar=yvar)
# N.ACS.plots_05_20_01 <- dim(alldata)[1] - n1
# N.Total.plots_05_20_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_20_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_20_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_20_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_20_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_20_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_20_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_20_01 = mean(temp$m)
# median_m_05_20_01 = median(temp$m)
# max_m_05_20_01 = max(temp$m)
# min_m_05_20_01 = min(temp$m)
# mean_uniq_m_05_20_01 = mean(unique(temp$m))
# median_uniq_m_05_20_01 = median(unique(temp$m))
# max_uniq_m_05_20_01 = max(unique(temp$m))
# min_uniq_m_05_20_01 = min(unique(temp$m))
# } else {
# mean_m_05_20_01 = NA
# median_m_05_20_01 = NA
# max_m_05_20_01 = NA
# min_m_05_20_01 = NA
# mean_uniq_m_05_20_01 = NA
# median_uniq_m_05_20_01 = NA
# max_uniq_m_05_20_01 = NA
# min_uniq_m_05_20_01 = NA
# }
#
#
#
# # sim 2
# seed_05_20_02 <- sim_seeds[2]
# #set.seed(seed_05_20_02)
# alldata <- createACS(popdata=popdata20, seed=seed_05_20_02, n1=n1, yvar=yvar)
# N.ACS.plots_05_20_02 <- dim(alldata)[1] - n1
# N.Total.plots_05_20_02 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_05_20_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_05_20_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_05_20_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_05_20_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_05_20_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_05_20_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_05_20_02 = mean(temp$m)
# median_m_05_20_02 = median(temp$m)
# max_m_05_20_02 = max(temp$m)
# min_m_05_20_02 = min(temp$m)
# mean_uniq_m_05_20_02 = mean(unique(temp$m))
# median_uniq_m_05_20_02 = median(unique(temp$m))
# max_uniq_m_05_20_02 = max(unique(temp$m))
# min_uniq_m_05_20_02 = min(unique(temp$m))
# } else {
# mean_m_05_20_02 = NA
# median_m_05_20_02 = NA
# max_m_05_20_02 = NA
# min_m_05_20_02 = NA
# mean_uniq_m_05_20_02 = NA
# median_uniq_m_05_20_02 = NA
# max_uniq_m_05_20_02 = NA
# min_uniq_m_05_20_02 = NA
# }
#
# # n1=10, popvar=20 --------------------------------------------------------------#
# tseed1 <- 2
# set.seed(tseed1)
# sim_seeds <- runif(sims)
#
# n1 <- 10
# popvar <- 20
#
# # sim 1
# seed_10_20_01 <- sim_seeds[1]
# #set.seed(seed_10_20_01)
# alldata <- createACS(popdata=popdata20, seed=seed_10_20_01, n1=n1, yvar=yvar)
# N.ACS.plots_10_20_01 <- dim(alldata)[1] - n1
# N.Total.plots_10_20_01 <- dim(alldata)[1]
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_20_01 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_20_01 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_20_01 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_20_01 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_20_01 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_20_01 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_20_01 = mean(temp$m)
# median_m_10_20_01 = median(temp$m)
# max_m_10_20_01 = max(temp$m)
# min_m_10_20_01 = min(temp$m)
# mean_uniq_m_10_20_01 = mean(unique(temp$m))
# median_uniq_m_10_20_01 = median(unique(temp$m))
# max_uniq_m_10_20_01 = max(unique(temp$m))
# min_uniq_m_10_20_01 = min(unique(temp$m))
# } else {
# mean_m_10_20_01 = NA
# median_m_10_20_01 = NA
# max_m_10_20_01 = NA
# min_m_10_20_01 = NA
# mean_uniq_m_10_20_01 = NA
# median_uniq_m_10_20_01 = NA
# max_uniq_m_10_20_01 = NA
# min_uniq_m_10_20_01 = NA
# }
#
#
#
# # sim 2
# seed_10_20_02 <- sim_seeds[2]
# #set.seed(seed_10_20_02)
# alldata <- createACS(popdata=popdata20, seed=seed_10_20_02, n1=n1, yvar=yvar)
# N.ACS.plots_10_20_02 <- dim(alldata)[1] - n1
# N.Total.plots_10_20_02 <- dim(alldata)[1]
#
#
# alldata_noedge <- alldata %>%
# filter(Sampling!="Edge")
# O_smd <- alldata %>%
# select(Cactus, Stricta, Pusilla, NetworkID, m) %>%
# filter(!(is.na(NetworkID))) %>%
# group_by(NetworkID) %>%
# filter(row_number()==1) %>%
# ungroup()
#
# Stricta_yHT_10_20_02 <- y_HT(y=alldata_noedge$Stricta, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Pusilla_yHT_10_20_02 <- y_HT(y=alldata_noedge$Pusilla, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Cactus_yHT_10_20_02 <- y_HT(y=alldata_noedge$Cactus, N = 900, n1 = n1, m_vec = alldata_noedge$m)
# Stricta_var_yHT_10_20_02 <- var_y_HT(O_smd$Stricta, N = 900, n1=n1, m_vec=O_smd$m)
# Pusilla_var_yHT_10_20_02 <- var_y_HT(O_smd$Pusilla, N = 900, n1=n1, m_vec=O_smd$m)
# Cactus_var_yHT_10_20_02 <- var_y_HT(O_smd$Cactus, N = 900, n1=n1, m_vec=O_smd$m)
#
# if (sum(alldata$Cactus) > 0) {
# temp <- alldata %>% filter(Cactus > 0)
# mean_m_10_20_02 = mean(temp$m)
# median_m_10_20_02 = median(temp$m)
# max_m_10_20_02 = max(temp$m)
# min_m_10_20_02 = min(temp$m)
# mean_uniq_m_10_20_02 = mean(unique(temp$m))
# median_uniq_m_10_20_02 = median(unique(temp$m))
# max_uniq_m_10_20_02 = max(unique(temp$m))
# min_uniq_m_10_20_02 = min(unique(temp$m))
# } else {
# mean_m_10_20_02 = NA
# median_m_10_20_02 = NA
# max_m_10_20_02 = NA
# min_m_10_20_02 = NA
# mean_uniq_m_10_20_02 = NA
# median_uniq_m_10_20_02 = NA
# max_uniq_m_10_20_02 = NA
# min_uniq_m_10_20_02 = NA
# }
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
# seed <- c(
# seed_05_05_01, seed_05_05_02,
# seed_10_05_01, seed_10_05_02,
#
# seed_05_10_01, seed_05_10_02,
# seed_10_10_01, seed_10_10_02,
#
# seed_05_15_01, seed_05_15_02,
# seed_10_15_01, seed_10_15_02,
#
# seed_05_20_01, seed_05_20_02,
# seed_10_20_01, seed_10_20_02
# )
#
# Stricta_yHT <- c(
# Stricta_yHT_05_05_01, Stricta_yHT_05_05_02,
# Stricta_yHT_10_05_01, Stricta_yHT_10_05_02,
#
# Stricta_yHT_05_10_01, Stricta_yHT_05_10_02,
# Stricta_yHT_10_10_01, Stricta_yHT_10_10_02,
#
# Stricta_yHT_05_15_01, Stricta_yHT_05_15_02,
# Stricta_yHT_10_15_01, Stricta_yHT_10_15_02,
#
# Stricta_yHT_05_20_01, Stricta_yHT_05_20_02,
# Stricta_yHT_10_20_01, Stricta_yHT_10_20_02
# )
#
# Pusilla_yHT <- c(
# Pusilla_yHT_05_05_01, Pusilla_yHT_05_05_02,
# Pusilla_yHT_10_05_01, Pusilla_yHT_10_05_02,
#
# Pusilla_yHT_05_10_01, Pusilla_yHT_05_05_02,
# Pusilla_yHT_10_10_01, Pusilla_yHT_10_05_02,
#
# Pusilla_yHT_05_15_01, Pusilla_yHT_05_15_02,
# Pusilla_yHT_10_15_01, Pusilla_yHT_10_15_02,
#
# Pusilla_yHT_05_20_01, Pusilla_yHT_05_20_02,
# Pusilla_yHT_10_20_01, Pusilla_yHT_10_20_02
# )
#
# Cactus_yHT <- c(
# Cactus_yHT_05_05_01, Cactus_yHT_05_05_02,
# Cactus_yHT_10_05_01, Cactus_yHT_10_05_02,
#
# Cactus_yHT_05_10_01, Cactus_yHT_05_10_02,
# Cactus_yHT_10_10_01, Cactus_yHT_10_10_02,
#
# Cactus_yHT_05_15_01, Cactus_yHT_05_15_02,
# Cactus_yHT_10_15_01, Cactus_yHT_10_15_02,
#
# Cactus_yHT_05_20_01, Cactus_yHT_05_20_02,
# Cactus_yHT_10_20_01, Cactus_yHT_10_20_02
# )
#
# Stricta_var_yHT <- c(
# Stricta_var_yHT_05_05_01, Stricta_var_yHT_05_05_02,
# Stricta_var_yHT_10_05_01, Stricta_var_yHT_10_05_02,
#
# Stricta_var_yHT_05_10_01, Stricta_var_yHT_05_10_02,
# Stricta_var_yHT_10_10_01, Stricta_var_yHT_10_10_02,
#
# Stricta_var_yHT_05_15_01, Stricta_var_yHT_05_15_02,
# Stricta_var_yHT_10_15_01, Stricta_var_yHT_10_15_02,
#
# Stricta_var_yHT_05_20_01, Stricta_var_yHT_05_20_02,
# Stricta_var_yHT_10_20_01, Stricta_var_yHT_10_20_02
# )
#
#
# Pusilla_var_yHT <- c(
# Pusilla_var_yHT_05_05_01, Pusilla_var_yHT_05_05_02,
# Pusilla_var_yHT_10_05_01, Pusilla_var_yHT_10_05_02,
#
# Pusilla_var_yHT_05_10_01, Pusilla_var_yHT_05_10_02,
# Pusilla_var_yHT_10_10_01, Pusilla_var_yHT_10_10_02,
#
# Pusilla_var_yHT_05_15_01, Pusilla_var_yHT_05_15_02,
# Pusilla_var_yHT_10_15_01, Pusilla_var_yHT_10_15_02,
#
# Pusilla_var_yHT_05_20_01, Pusilla_var_yHT_05_20_02,
# Pusilla_var_yHT_10_20_01, Pusilla_var_yHT_10_20_02
# )
#
# Cactus_var_yHT <- c(
# Cactus_var_yHT_05_05_01, Cactus_var_yHT_05_05_02,
# Cactus_var_yHT_10_05_01, Cactus_var_yHT_10_05_02,
#
# Cactus_var_yHT_05_10_01, Cactus_var_yHT_05_10_02,
# Cactus_var_yHT_10_10_01, Cactus_var_yHT_10_10_02,
#
# Cactus_var_yHT_05_15_01, Cactus_var_yHT_05_15_02,
# Cactus_var_yHT_10_15_01, Cactus_var_yHT_10_15_02,
#
# Cactus_var_yHT_05_20_01, Cactus_var_yHT_05_20_02,
# Cactus_var_yHT_10_20_01, Cactus_var_yHT_10_20_02
# )
#
# mean_m <- c(
# mean_m_05_05_01, mean_m_05_05_02,
# mean_m_10_05_01, mean_m_10_05_02,
#
# mean_m_05_10_01, mean_m_05_10_02,
# mean_m_10_10_01, mean_m_10_10_02,
#
# mean_m_05_15_01, mean_m_05_15_02,
# mean_m_10_15_01, mean_m_10_15_02,
#
# mean_m_05_20_01, mean_m_05_20_02,
# mean_m_10_20_01, mean_m_10_20_02
# )
#
# median_m <- c(
# median_m_05_05_01, median_m_05_05_02,
# median_m_10_05_01, median_m_10_05_02,
#
# median_m_05_10_01, median_m_05_10_02,
# median_m_10_10_01, median_m_10_10_02,
#
# median_m_05_15_01, median_m_05_15_02,
# median_m_10_15_01, median_m_10_15_02,
#
# median_m_05_20_01, median_m_05_20_02,
# median_m_10_20_01, median_m_10_20_02
# )
#
# max_m <- c(
# max_m_05_05_01, max_m_05_05_02,
# max_m_10_05_01, max_m_10_05_02,
#
# max_m_05_10_01, max_m_05_10_02,
# max_m_10_10_01, max_m_10_10_02,
#
# max_m_05_15_01, max_m_05_15_02,
# max_m_10_15_01, max_m_10_15_02,
#
# max_m_05_20_01, max_m_05_20_02,
# max_m_10_20_01, max_m_10_20_02
# )
#
# min_m <- c(
# min_m_05_05_01, min_m_05_05_02,
# min_m_10_05_01, min_m_10_05_02,
#
# min_m_05_10_01, min_m_05_10_02,
# min_m_10_10_01, min_m_10_10_02,
#
# min_m_05_15_01, min_m_05_15_02,
# min_m_10_15_01, min_m_10_15_02,
#
# min_m_05_20_01, min_m_05_20_02,
# min_m_10_20_01, min_m_10_20_02
# )
#
# mean_uniq_m <- c(
# mean_uniq_m_05_05_01, mean_uniq_m_05_05_02,
# mean_uniq_m_10_05_01, mean_uniq_m_10_05_02,
#
# mean_uniq_m_05_10_01, mean_uniq_m_05_10_02,
# mean_uniq_m_10_10_01, mean_uniq_m_10_10_02,
#
# mean_uniq_m_05_15_01, mean_uniq_m_05_15_02,
# mean_uniq_m_10_15_01, mean_uniq_m_10_15_02,
#
# mean_uniq_m_05_20_01, mean_uniq_m_05_20_02,
# mean_uniq_m_10_20_01, mean_uniq_m_10_20_02
# )
#
# median_uniq_m <- c(
# median_uniq_m_05_05_01, median_uniq_m_05_05_02,
# median_uniq_m_10_05_01, median_uniq_m_10_05_02,
#
# median_uniq_m_05_10_01, median_uniq_m_05_10_02,
# median_uniq_m_10_10_01, median_uniq_m_10_10_02,
#
# median_uniq_m_05_15_01, median_uniq_m_05_15_02,
# median_uniq_m_10_15_01, median_uniq_m_10_15_02,
#
# median_uniq_m_05_20_01, median_uniq_m_05_20_02,
# median_uniq_m_10_20_01, median_uniq_m_10_20_02
# )
#
# max_uniq_m <- c(
# max_uniq_m_05_05_01, max_uniq_m_05_05_02,
# max_uniq_m_10_05_01, max_uniq_m_10_05_02,
#
# max_uniq_m_05_10_01, max_uniq_m_05_10_02,
# max_uniq_m_10_10_01, max_uniq_m_10_10_02,
#
# max_uniq_m_05_15_01, max_uniq_m_05_15_02,
# max_uniq_m_10_15_01, max_uniq_m_10_15_02,
#
# max_uniq_m_05_20_01, max_uniq_m_05_20_02,
# max_uniq_m_10_20_01, max_uniq_m_10_20_02
# )
#
# min_uniq_m <- c(
# min_uniq_m_05_05_01, min_uniq_m_05_05_02,
# min_uniq_m_10_05_01, min_uniq_m_10_05_02,
#
# min_uniq_m_05_10_01, min_uniq_m_05_10_02,
# min_uniq_m_10_10_01, min_uniq_m_10_10_02,
#
# min_uniq_m_05_15_01, min_uniq_m_05_15_02,
# min_uniq_m_10_15_01, min_uniq_m_10_15_02,
#
# min_uniq_m_05_20_01, min_uniq_m_05_20_02,
# min_uniq_m_10_20_01, min_uniq_m_10_20_02
# )
#
# N.ACS.plots <- c(
# N.ACS.plots_05_05_01, N.ACS.plots_05_05_02,
# N.ACS.plots_10_05_01, N.ACS.plots_10_05_02,
#
# N.ACS.plots_05_10_01, N.ACS.plots_05_10_02,
# N.ACS.plots_10_10_01, N.ACS.plots_10_10_02,
#
# N.ACS.plots_05_15_01, N.ACS.plots_05_15_02,
# N.ACS.plots_10_15_01, N.ACS.plots_10_15_02,
#
# N.ACS.plots_05_20_01, N.ACS.plots_05_20_02,
# N.ACS.plots_10_20_01, N.ACS.plots_10_20_02
# )
#
# N.Total.plots <- c(
# N.Total.plots_05_05_01, N.Total.plots_05_05_02,
# N.Total.plots_10_05_01, N.Total.plots_10_05_02,
#
# N.Total.plots_05_10_01, N.Total.plots_05_10_02,
# N.Total.plots_10_10_01, N.Total.plots_10_10_02,
#
# N.Total.plots_05_15_01, N.Total.plots_05_15_02,
# N.Total.plots_10_15_01, N.Total.plots_10_15_02,
#
# N.Total.plots_05_20_01, N.Total.plots_05_20_02,
# N.Total.plots_10_20_01, N.Total.plots_10_20_02
# )
#
#
# simulation_data %<>%
# dplyr::select(
# -c(JoinCountTest.S, MoranI.S, SimDate)
# )
#
# # simulation_data %<>%
# # dplyr::select(
# # -c(mean_m,
# # median_m,
# # max_m,
# # min_m,
# # mean_uniq_m,
# # median_uniq_m,
# # max_uniq_m,
# # min_uniq_m
# # #JoinCountTest.S,
# # )
# # )
#
#
# manually_calculated <- data.frame(
# Stricta_yHT,
# Pusilla_yHT,
# Cactus_yHT,
# Stricta_var_yHT,
# Pusilla_var_yHT,
# Cactus_var_yHT,
# Plots = "Horvitz Thompson Mean (All Plots)",
# simulation = rep(1:2, 2),
# seed,
# N.ACS.plots,
# N.Total.plots,
# realvar = 1,
# popvar = c(rep(5,4), rep(10, 4), rep(15, 4), rep(20, 4)),
# N.SRSWOR.plots = rep(c(rep(5, 2), rep(10, 2)), 4),
# mean_m,
# median_m,
# max_m,
# min_m,
# mean_uniq_m,
# median_uniq_m,
# max_uniq_m,
# min_uniq_m,
# #JoinCountTest.S,
# #MoranI.S,
# f_max = 2,
# nSims = 2,
# y_HT_formula = "y_HT",
# SamplingDesign = "ACS",
# MoransIWeightMatrix = weights
# )
#
#
# test_that("test sampleRealizations", {
# expect_equal(
# simulation_data,
# manually_calculated
# )
# })
#
# popvar = "n.networks"
# realvar = "realization"
#
# simulation_data_sample_estimators <- sampleRealizations(
# popdata=popdata,
# sims=sims,
# n1_vec=n1_vec,
# avar=avar,
# ovar=ovar,
# rvar=rvar,
# #ACS=TRUE,
# SamplingDesign=SamplingDesign,
# yvar=yvar,
# y_HT_formula=y_HT_formula,
# var_formula=var_formula,
# m_threshold=m_threshold,
# f_max=f_max,
# SampleEstimators=TRUE,
# SpatStat=SpatStat,
# mChar=mChar,
# popvar=popvar,
# realvar=realvar,
# weights=weights,
# seed=seed
# )
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