calcMV: Calculate information required for plotting PCA biplot with...

In MiguelRodo/ggboot: Bootstrap univariate and multivariate plots

Calculate information required for plotting PCA biplot with confidence areas.

Description

Calculate information required for plotting PCA biplot with confidence areas.

Usage

calcMV(data, group, B, seed, comp = 1:2, scale, calcLoc, boot = TRUE,
  save = FALSE, name = NULL, env = NULL, path = NULL, quant, trim)

Arguments

data	dataframe. Only the numeric columns will be used.
group	vector. Vector indicating group membership for each observation in data. Will be coerced to a character vector.
B	integer. Number of bootstrap samples per subgroup.
comp	integer vector. Specifies the principal components whose proportion of variation must be returned. Defaults to 1:2.
boot	logical. If TRUE, then bootstrap is re-performed. If FALSE, then bootstrap values are taken from object with name name in environment bootList.
save	logical. If TRUE and boot=TRUE, then bootList is
name	character. Name of object in bootList to add to or take to. Must not be NULL if save=TRUE.
env	environment. Environment to save bootstrapped values to.
path	character. Path of to save bootstrapped values to, or load bootstrapped values from.
quant	logical. If TRUE, then univariate 95 percent percentile bootstrap confidence intervals are plotted.

MiguelRodo/ggboot documentation built on Nov. 9, 2023, 5:45 p.m.