| loadingplot.Coxmos {Coxmos} | R Documentation |
loadingplot.Coxmos
Description
The loadingplot.Coxmos function visualizes the loading values of a given Coxmos model. The
function produces a series of bar plots for each component's loading values, offering a
comprehensive view of the model's variable contributions. The plots can be customized to exclude
zero loadings, display only the top variables, and automatically adjust the color scale limits.
Usage
loadingplot.Coxmos(model, zero.rm = TRUE, top = NULL, auto.limits = TRUE)
Arguments
model |
Coxmos model. |
zero.rm |
Logical. Remove variables equal to 0 (default: TRUE). |
top |
Numeric. Show "top" first variables. If top = NULL, all variables are shown (default: NULL). |
auto.limits |
Logical. If "auto.limits" = TRUE, limits are detected automatically (default: TRUE). |
Details
The primary objective of the loadingplot.Coxmos function is to facilitate the interpretation of
Coxmos models by visualizing the loading values of each component. The function first verifies the
class of the provided model to ensure it is a valid Coxmos model.
The loading values are extracted from the model and processed based on the user's specifications.
If the zero.rm parameter is set to TRUE, variables with zero loadings are excluded from the
visualization. Additionally, if the top parameter is specified, only the top variables, ranked
by their absolute loading values, are displayed.
The function employs the 'ggplot2' framework for visualization. The color scale of the plots can be
automatically adjusted based on the maximum absolute loading value when auto.limits is set to
TRUE. If the RColorConesa package is available, it utilizes its color palettes for enhanced
visualization; otherwise, default colors are applied.
Value
A list of ggplot2 objects, each representing the loading values for a component of
the Coxmos model.
Examples
data("X_proteomic")
data("Y_proteomic")
X <- X_proteomic[,1:50]
Y <- Y_proteomic
splsicox.model <- splsicox(X, Y, n.comp = 2, penalty = 0.5, x.center = TRUE, x.scale = TRUE)
loadingplot.Coxmos(model = splsicox.model)