Plot the training results, the black line is the 1:1 line, the red line is the linear regression line to fitted and x, which shows the degree of overall compression.

plot_train(train_output, col)

## Arguments

train_output

Training output, can be the output of WA-PLS, WA-PLS with fx correction, TWA-PLS, or TWA-PLS with fx correction.

col

Choose which column of the fitted value to plot, in other words, how many number of components you want to use.

## Value

Plotting status.

TWAPLS.w and WAPLS.w

## Examples

if (FALSE) {

# Extract taxa
taxaColMin <- which(colnames(modern_pollen) == "taxa0")
taxaColMax <- which(colnames(modern_pollen) == "taxaN")
taxa <- modern_pollen[, taxaColMin:taxaColMax]

fit_tf_Tmin2 <- fxTWAPLS::TWAPLS.w2(
taxa,
modern_pollen\$Tmin,
nPLS = 5,
usefx = TRUE,
fx_method = "bin",
bin = 0.02
)

nsig <- 3 # This should be got from the random t-test of the cross validation
fxTWAPLS::plot_train(fit_tf_Tmin2, nsig)
}