plot_correlations: Plots design diagnostics

In skpr: Design of Experiments Suite: Generate and Evaluate Optimal Designs

Plots design diagnostics

Description

Plots design diagnostics

Usage

plot_correlations(
  genoutput,
  model = NULL,
  customcolors = NULL,
  pow = 2,
  custompar = NULL,
  standardize = TRUE
)

Arguments

genoutput	The output of either gen_design or eval_design/eval_design_mc
model	Default 'NULL'. Defaults to the model used in generating/evaluating the design, augmented with 2-factor interactions. If specified, it will override the default model used to generate/evaluate the design.
customcolors	A vector of colors for customizing the appearance of the colormap
pow	Default 2. The interaction level that the correlation map is showing.
custompar	Default NULL. Custom parameters to pass to the 'par' function for base R plotting.
standardize	Default 'TRUE'. Whether to standardize (scale to -1 and 1 and center) the continuous numeric columns. Not standardizing the numeric columns can increase multi-collinearity (predictors that are correlated with other predictors in the model).

Value

Silently returns the correlation matrix with the proper row and column names.

Examples

#We can pass either the output of gen_design or eval_design to plot_correlations
#in order to obtain the correlation map. Passing the output of eval_design is useful
#if you want to plot the correlation map from an externally generated design.

#First generate the design:

candidatelist = expand.grid(cost = c(15000, 20000), year = c("2001", "2002", "2003", "2004"),
                           type = c("SUV", "Sedan", "Hybrid"))
cardesign = gen_design(candidatelist, ~(cost+type+year)^2, 30)
plot_correlations(cardesign)

#We can also increase the level of interactions that are shown by default.

plot_correlations(cardesign, pow = 3)

#You can also pass in a custom color map.
plot_correlations(cardesign, customcolors = c("blue", "grey", "red"))
plot_correlations(cardesign, customcolors = c("blue", "green", "yellow", "orange", "red"))

skpr documentation built on July 9, 2023, 7:23 p.m.