Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width=6,
fig.height=4
)
## ----setup--------------------------------------------------------------------
library(soiltestcorr)
## ----warning=FALSE, message=FALSE---------------------------------------------
# Install if needed
library(ggplot2) # Plots
library(dplyr) # Data wrangling
library(tidyr) # Data wrangling
library(utils) # Data wrangling
library(purrr) # Mapping
## -----------------------------------------------------------------------------
# Example 1 dataset
# Fake dataset manually created
data_1 <- data.frame("RY" = c(65,80,85,88,90,94,93,96,97,95,98,100,99,99,100),
"STV" = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15))
# Example 2. Native fake dataset from soiltestcorr package
data_2 <- soiltestcorr::data_test
# Example 3. Native dataset from soiltestcorr package, Freitas et al. (1966), used by Cate & Nelson (1971)
data_3 <- soiltestcorr::freitas1966
## ----warning=TRUE, message=TRUE-----------------------------------------------
# Using dataframe argument, tidy = FALSE -> return a LIST
fit_1_tidy_false <-
soiltestcorr::cate_nelson_1971(data = data_1,
ry = RY,
stv = STV,
tidy = FALSE)
utils::head(fit_1_tidy_false)
## ----warning=TRUE, message=TRUE-----------------------------------------------
# Using dataframe argument, tidy = FALSE -> return a LIST
fit_1_tidy_true <-
soiltestcorr::cate_nelson_1971(data = data_1,
ry = RY,
stv = STV,
tidy = TRUE)
utils::head(fit_1_tidy_true)
## ----warning=TRUE, message=TRUE-----------------------------------------------
fit_1_vectors_list <-
soiltestcorr::cate_nelson_1971(ry = data_1$RY,
stv = data_1$STV,
tidy = FALSE)
fit_1_vectors_tidy <-
soiltestcorr::cate_nelson_1971(ry = data_1$RY,
stv = data_1$STV,
tidy = TRUE)
## ----warning=TRUE, message=TRUE-----------------------------------------------
fit_2 <-
soiltestcorr::cate_nelson_1971(data = data_2,
ry = RY,
stv = STV,
tidy = TRUE)
utils::head(fit_2)
## ----warning=TRUE, message=TRUE-----------------------------------------------
fit_3 <-
soiltestcorr::cate_nelson_1971(data = data_3,
ry = RY,
stv = STK,
tidy = TRUE)
utils::head(fit_3)
## ----warning=T, message=F-----------------------------------------------------
#
data.all <- dplyr::bind_rows(data_1, data_2,
data_3 %>% dplyr::rename(STV = STK),
.id = "id") %>%
tidyr::nest(data = c("STV", "RY"))
## ----warning=T, message=F-----------------------------------------------------
# Run multiple examples at once with map()
fit_multiple_map <- data.all %>%
dplyr::mutate(mod_alcc = purrr::map(data,
~ soiltestcorr::cate_nelson_1971(ry = .$RY,
stv = .$STV,
tidy = TRUE)))
utils::head(fit_multiple_map)
## ----warning=T, message=F-----------------------------------------------------
fit_multiple_group_map <-
data.all %>% tidyr::unnest(data) %>%
#dplyr::bind_rows(data_1, data_2, .id = "id") %>%
dplyr::group_by(id) %>%
dplyr::group_modify(~ soiltestcorr::cate_nelson_1971(data = .,
ry = RY,
stv = STV,
tidy = TRUE))
utils::head(fit_multiple_group_map)
## -----------------------------------------------------------------------------
boot_cn71 <- soiltestcorr::boot_cn_1971(data = data_1,
ry = RY, stv = STV, n = 99)
boot_cn71 %>% dplyr::slice_head(., n=5)
# CSTV Confidence Interval
quantile(boot_cn71$CSTV, probs = c(0.025, 0.5, 0.975))
# Plot
boot_cn71 %>%
ggplot2::ggplot(aes(x = CSTV))+
geom_histogram(color = "grey25", fill = "#9de0bf", bins = 10)
## ----warning=F, message=F-----------------------------------------------------
soiltestcorr::cate_nelson_1971(data = data_1,
ry = RY,
stv = STV,
plot = TRUE)
soiltestcorr::cate_nelson_1971(data = data_2,
ry = RY,
stv = STV,
plot = TRUE)
soiltestcorr::cate_nelson_1971(data = data_3,
ry = RY,
stv = STK,
plot = TRUE)
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