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)`

- 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.

Plotting status.

```
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]
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)
}
```