cv.w | R Documentation |
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 )
modern_taxa |
The modern taxa abundance data, each row represents a sampling site, each column represents a taxon. |
modern_climate |
The modern climate value at each sampling site. |
nPLS |
The number of components to be extracted. |
trainfun |
Training function you want to use, either
|
predictfun |
Predict function you want to use: if |
usefx |
Boolean flag on whether or not use |
fx_method |
Binned or p-spline smoothed |
bin |
Binwidth to get fx, needed for both binned and p-splined method.
if |
cpus |
Number of CPUs for simultaneous iterations to execute, check
|
test_mode |
boolean flag to execute the function with a limited number
of iterations, |
test_it |
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
## Not run: # 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() ## End(Not run)
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