sig.dim.perm: Permuted significance of CA dimensions

In CAinterprTools: Graphical Aid in Correspondence Analysis Interpretation and Significance Testings

Description

This function calculates the permuted significance of a pair of selected CA dimensions. Number of permutation set at 999 by default, but can be increased by the user. A scatterplot of the permuted inertia of a pair of selected dimensions is produced. Permuted p.values are reported in the axes' labels and are also returned in a dataframe.

Usage

sig.dim.perm(data, x = 1, y = 2, B = 999)

Arguments

data	Name of the dataset (must be in dataframe format).
x	First dimension whose significance is calculated (x=1 by default).
y	Second dimension whose significance is calculated (y=2 by default).
B	Number of permutations (999 by default).

Value

The function returns a dataframe storing the permuted p-values of each CA dimension.

See Also

sig.dim.perm.scree

Examples

data(greenacre_data)

#Produces a scatterplot of the permuted inertia of the 1 CA dimension
#against the permuted inertia of the 2 CA dimension.
#The observed inertia of the selected dimensions is displayed as a large red dot; 
#pvalues are reported in the axes labels (and are stored in a 'pvalues' object).

pvalues <- sig.dim.perm(greenacre_data, 1,2, B=99)

CAinterprTools documentation built on July 8, 2020, 5:15 p.m.