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PLSDA predicted plot

Source: R/PLSDA_charts.R
plsda_predicted_plot.Rd

A plot of the regression coefficients from a PLSDA model.

Usage

plsda_predicted_plot(factor_name, style = "boxplot", ycol = 1, ...)

Arguments

factor_name

(character) The name of a sample-meta column to use.

style

(character) Plot style. Allowed values are limited to the following:

  • "boxplot": A boxplot.

  • "violin": A violin plot.

  • "density": A density plot.

The default is "boxplot".

ycol

(character, numeric, integer) The column of the Y block to be plotted. The default is 1.

...

Additional slots and values passed to struct_class.

Value

A plsda_predicted_plot object. This object has no output slots. See chart_plot in the struct package to plot this chart object.

Details

This object makes use of functionality from the following packages:

  • pls

  • ggplot2

Inheritance

A plsda_predicted_plot object inherits the following struct classes:

[plsda_predicted_plot] >> [chart] >> [struct_class]

References

Liland K, Mevik B, Wehrens R (2023). pls: Partial Least Squares and Principal Component Regression. R package version 2.8-3, https://CRAN.R-project.org/package=pls.

Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.

Examples

M = plsda_predicted_plot(
      factor_name = "V1",
      style = "boxplot",
      ycol = 1)

D = iris_DatasetExperiment()
M = mean_centre()+PLSDA(factor_name='Species')
M = model_apply(M,D)

C = plsda_predicted_plot(factor_name='Species')
chart_plot(C,M[2])