Skip to contents

Plot Basic Transformations of Predictor Variables for GAM Modelling

plot_transformations.Rd

This function generates diagnostic plots to visualise the distribution of predictor variables and the effects of basic transformations (square root and log transformations) on these variables. It creates scatter plots and histograms for the raw, square root, and log-transformed data. The function is useful for exploring the suitability of different transformations before fitting a Generalized Additive Model (GAM).

Usage

plot_transformations(pred.vars, dat)

Arguments

pred.vars

A character vector of predictor variable names to be plotted.

dat

A data frame containing the predictor variables and a grouping variable, either 'opcode' or 'sample', which is used for the scatter plots.

Value

The function generates and prints diagnostic plots but does not return a value.

Examples

if (FALSE) { # \dontrun{
# Assuming 'dat' is a data frame containing the predictor variables and 'opcode' or 'sample' column
plot_transformations(pred.vars = c("var1", "var2"), dat = dat)
} # }