MultipleCorrespondenceAnalysis: 'MultipleCorrespondanenceAnalysis'

In Displayr/flipDimensionReduction: Algorithms for dimension reduction

MultipleCorrespondanenceAnalysis

Description

Calculate multiple correspondence analysis of categorical variables

Usage

MultipleCorrespondenceAnalysis(
  formula,
  data = NULL,
  output = c("Text", "Scatterplot")[1],
  scatter.palette = "Default colors",
  weights = NULL,
  subset = NULL,
  missing = "Exclude cases with missing data",
  auxiliary.data = NULL,
  chart.title = "Multiple correspondence analysis",
  max.labels.plot = 200,
  show.labels = FALSE
)

## S3 method for class 'mcaObj'
fitted(object, ...)

Arguments

formula	Symbolic description of the model to be fitted
data	A data frame containing factor variables.
output	Specify output generated. May be one of "Scatterplot" or "Text".
scatter.palette	Color palette used for Scatterplot output.
weights	A numeric vector containing the weight for each case in data.
subset	A logical vector which describes the subset of data to be analysed.
missing	A string specifiying what to do when the data contains missing values. This should be one of "Error if missing data", "Exclude cases with missing data", and "Imputation (replace missing values with estimates)".
auxiliary.data	A data.frame containing additional variables to be used in imputation (if required). While adding more variables will improve the quality of the imputation, it will dramatically slow down the time to estimate. Factors and Character variables with a large number of categories should not be included, as they will both slow down the data and are unlikely to be useful
chart.title	String used as the title of the Scatterplot.
max.labels.plot	A number specifying the maximum of labels of show in bubble or scatterplots. The remaining points will be shown without labels.
show.labels	A logical indicating whether "Label" attribute should be used for reporting results
object	Object of class "mcaObj" created using MultipleComponentsAnalysis.
...	Not used.

Displayr/flipDimensionReduction documentation built on March 2, 2024, 3:50 a.m.