reduceDimensionality {psichomics}R Documentation

Reduce dimensionality after processing missing values from data frame

Description

Reduce dimensionality after processing missing values from data frame

Usage

reduceDimensionality(data, type = c("pca", "ica"), center = TRUE,
  scale. = FALSE, naTolerance = NULL, missingValues = round(0.05 *
  ncol(data)), ...)

Arguments

data

Data frame: data

type

Character: dimensionality reduction technique (pca or ica)

center

either a logical value or numeric-alike vector of length equal to the number of columns of x, where ‘numeric-alike’ means that as.numeric(.) will be applied successfully if is.numeric(.) is not true.

scale.

Boolean: scale variables?

naTolerance

Integer: percentage of tolerated missing values per column (deprecated)

missingValues

Integer: number of tolerated missing values per column to be replaced with the mean of the values of that same column (5 rows by default)

...

Extra parameters passed to FUN

Value

PCA result in a prcomp object or ICA result object


[Package psichomics version 1.9.1 Index]