Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(dynamicSDM)
## ----create directories-------------------------------------------------------
project_directory <- file.path(file.path(tempdir(), "dynamicSDM_vignette"))
# project_directory<-"your_path_here"
dir.create(project_directory)
#sample_explan_data <- read.csv(paste0(project_directory, "/extracted_quelea_occ.csv"))
## ----import explanatory data--------------------------------------------------
data("sample_explan_data")
## ----example-spatiotemp_autocorr----------------------------------------------
variablenames<-c("eight_sum_prec","year_sum_prec","grass_crop_percentage")
autocorrelation <- spatiotemp_autocorr(sample_explan_data,
varname = variablenames,
plot = TRUE,
temporal.level = c("year")) # can choose month or day too
autocorrelation
## ----example-spatiotemp_block-------------------------------------------------
data("sample_extent_data")
random_cat_layer <- terra::rast(sample_extent_data)
random_cat_layer <- terra::setValues(random_cat_layer,
sample(0:10, terra::ncell(random_cat_layer),
replace = TRUE))
sample_explan_data <- spatiotemp_block(sample_explan_data,
spatial.layer = random_cat_layer,
spatial.split.degrees = 3,
vars.to.block.by = variablenames,
temporal.block = "month",
n.blocks = 3,
iterations = 5000)
## ----example-brt_fit----------------------------------------------------------
sample_explan_data$weights <- (1 - sample_explan_data$REL_SAMP_EFFORT)
models <- brt_fit(sample_explan_data,
response.col = "presence.absence",
varnames = variablenames,
block.col = "BLOCK.CATS",
weights.col = "weights",
distribution = "bernoulli",
interaction.depth = 2)
## ----save models, eval=F------------------------------------------------------
# saveRDS(models, file = paste0(project_directory, "/fitted_quelea_SDMs.rds"))
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