mca: Multiple Correspondence Analysis

In hyunsooseol/snowCluster: Multivariate Analysis

Multiple Correspondence Analysis

Description

Multiple Correspondence Analysis

Usage

mca(
  data,
  facs,
  vars,
  nd = 2,
  eigen = TRUE,
  rowvar = "coordinates",
  loadingind = FALSE,
  colvar = "coordinates",
  loadingvar = FALSE,
  plot1 = FALSE,
  plot2 = FALSE,
  plot3 = FALSE,
  plot4 = FALSE,
  plot5 = TRUE,
  plot6 = FALSE,
  width1 = 500,
  height1 = 500,
  width2 = 500,
  height2 = 500,
  width3 = 500,
  height3 = 500,
  width4 = 500,
  height4 = 500,
  width5 = 500,
  height5 = 500,
  width6 = 500,
  height6 = 500
)

Arguments

data	The data as a data frame.
facs	.
vars	.
nd	.
eigen	.
rowvar	.
loadingind	.
colvar	.
loadingvar	.
plot1	.
plot2	.
plot3	.
plot4	.
plot5	.
plot6	.
width1	.
height1	.
width2	.
height2	.
width3	.
height3	.
width4	.
height4	.
width5	.
height5	.
width6	.
height6	.

Value

A results object containing:

results$instructions					a html
results$eigen					a table
results$loadingvar					a table
results$loadingind					a table
results$plot5					an image
results$plot6					an image
results$plot1					an image
results$plot2					an image
results$plot3					an image
results$plot4					an image

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$eigen$asDF

as.data.frame(results$eigen)

hyunsooseol/snowCluster documentation built on April 5, 2025, 2:06 a.m.