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Correlplot (version 1.1.0)

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

413

Version

1.1.0

License

GPL (>= 2)

Homepage

https://www.r-project.org

Maintainer

Jan Graffelman

Last Published

January 23rd, 2024

Functions in Correlplot (1.1.0)

Correlations between educational and demographic variables

Plot a correlogram

Create a correlation tally stick on a biplot vector

Correlations between characteristics of aircraft

Correlations between size measurements of archeological goblets

Fit angles to a correlation matrix

Characteristics of aircraft

Swiss banknote data

Correlations between thirtheen fysiological variables

Correlations between sources of protein

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

Establish limits for x and y axis

Create a biplot with ggplot2

Heights of mothers and daughters

Correlations between sources of protein

Low-rank matrix approximation by weighted alternating least squares

Linearized cosine function

Create a correlogram as a ggplot object.

Correlations between national track records for men

Correlations between marks for 5 exams

Marks for 5 student exams

Calculate the root mean squared error

Compute the trace of a matrix

Create a tally on a biplot vector

Principal Coordinate Analysis

Correlation matrix for boys of the Berkeley Guidance Study

Correlation matrix for height and length

Principal factor analysis

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

Correlations between three variables

Myocardial infarction or Heart attack data

Correlations for 10 generated variables

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

Convert angles to correlations.

FitRwithPCAandWALS

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

Wheat kernel data

Correlation matrix of characteristics of Australian athletes

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