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Correlplot (version 1.1.2)

A Collection of Functions for Graphing Correlation Matrices

Description

Routines for the graphical representation of correlation matrices by means of correlograms, MDS maps and biplots obtained by PCA, PFA or WALS (weighted alternating least squares); See Graffelman & De Leeuw (2023) .

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Version

Install

install.packages('Correlplot')

Monthly Downloads

501

Version

1.1.2

License

GPL (>= 2)

Homepage

https://www.r-project.org

Maintainer

Jan Graffelman

Last Published

July 25th, 2025

Functions in Correlplot (1.1.2)

Create a biplot with ggplot2

Wheat kernel data

Correlations between sources of protein

Correlations between sources of protein

Swiss banknote data

Correlation matrix of characteristics of Australian athletes

Heights of mothers and daughters

Correlation matrix for boys of the Berkeley Guidance Study

Linearized cosine function

Create a correlogram as a ggplot object.

Marks for 5 student exams

Correlation matrix for height and length

Function for obtaining a weighted least squares low-rank approximation of a symmetric matrix

Correlations between national track records for men

Establish limits for x and y axis

Create a correlation tally stick on a biplot vector

Correlations between size measurements of archeological goblets

Low-rank matrix approximation by weighted alternating least squares

Correlations between thirtheen fysiological variables

Correlations between marks for 5 exams

Correlations between three variables

Calculate the root mean squared error

Generate a table of root mean square error (RMSE) statistics for principal component analysis (PCA) and weighted alternating least squares (WALS).

Principal factor analysis

Principal Coordinate Analysis

Create a tally on a biplot vector

Compute the trace of a matrix

Program Keller calculates a rank p approximation to a correlation matrix according to Keller's method.

Correlations between characteristics of aircraft

Myocardial infarction or Heart attack data

Approximation of a correlation matrix with column adjustment and symmetric low rank factorization

FitRwithPCAandWALS

Calculate a low-rank approximation to the correlation matrix with four methods

Characteristics of aircraft

Correlations for 10 generated variables

Correlations between educational and demographic variables

Convert angles to correlations.

Fit angles to a correlation matrix

Plot a correlogram