Leave-one-out cross-validation as
rioja (https://cran.r-project.org/package=rioja).
cv.w(
modern_taxa,
modern_climate,
nPLS = 5,
trainfun,
predictfun,
usefx = FALSE,
fx_method = "bin",
bin = NA,
cpus = 4,
test_mode = FALSE,
test_it = 5
)The modern taxa abundance data, each row represents a sampling site, each column represents a taxon.
The modern climate value at each sampling site.
The number of components to be extracted.
Training function you want to use, either
WAPLS.w or TWAPLS.w.
Predict function you want to use: if trainfun is
WAPLS.w, then this should be WAPLS.predict.w;
if trainfun is TWAPLS.w, then this should be
TWAPLS.predict.w.
Boolean flag on whether or not use fx correction.
Binned or p-spline smoothed fx correction: if
usefx = FALSE, this should be NA; otherwise,
fx function will be used when choosing "bin";
fx_pspline function will be used when choosing "pspline".
Binwidth to get fx, needed for both binned and p-splined method.
if usefx = FALSE, this should be NA;
Number of CPUs for simultaneous iterations to execute, check
parallel::detectCores() for available CPUs on your machine.
boolean flag to execute the function with a limited number
of iterations, test_it, for testing purposes only.
number of iterations to use in the test mode.
leave-one-out cross validation results
fx, TWAPLS.w,
TWAPLS.predict.w, WAPLS.w, and
WAPLS.predict.w
if (FALSE) {
# Load modern pollen data
modern_pollen <- read.csv("/path/to/modern_pollen.csv")
# Extract taxa
taxaColMin <- which(colnames(modern_pollen) == "taxa0")
taxaColMax <- which(colnames(modern_pollen) == "taxaN")
taxa <- modern_pollen[, taxaColMin:taxaColMax]
## LOOCV
test_mode <- TRUE # It should be set to FALSE before running
cv_tf_Tmin2 <- fxTWAPLS::cv.w(
taxa,
modern_pollen$Tmin,
nPLS = 5,
fxTWAPLS::TWAPLS.w2,
fxTWAPLS::TWAPLS.predict.w,
usefx = TRUE,
fx_method = "bin",
bin = 0.02,
cpus = 2, # Remove the following line
test_mode = test_mode
)
# Run with progress bar
`%>%` <- magrittr::`%>%`
cv_tf_Tmin2 <- fxTWAPLS::cv.w(
taxa,
modern_pollen$Tmin,
nPLS = 5,
fxTWAPLS::TWAPLS.w2,
fxTWAPLS::TWAPLS.predict.w,
usefx = TRUE,
fx_method = "bin",
bin = 0.02,
cpus = 2, # Remove the following line
test_mode = test_mode
) %>% fxTWAPLS::pb()
}