Learn R Programming
⚠️There's a newer version (5.5) of this package.Take me there.

Compositional (version 3.1)

Compositional Data Analysis

Description

Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. The standard textbook for such data is John Aitchison's (1986). "The statistical analysis of compositional data". Chapman & Hall.

Copy Link

Version

Install

install.packages('Compositional')

Monthly Downloads

1,183

Version

3.1

License

GPL (>= 2)

Maintainer

Michail Tsagris

Last Published

June 4th, 2018

Functions in Compositional (3.1)

Ridge regression with the alpha-transformation plot

Ridge regression plot
Density values of a Dirichlet distribution

Density values of a Dirichlet distribution
The k-NN algorithm for compositional data

The k-NN algorithm for compositional data
Helper functions for the Kullback-Leibler regression

Helper functions for the Kullback-Leibler regression
Dirichlet regression

Dirichlet regression
Tuning of the principal components regression

Tuning of the principal components regression
Hypothesis testing for two or more compositional mean vectors

Hypothesis testing for two or more compositional mean vectors
Simulation of compositional data from Gaussian mixture models

Simulation of compositional data from Gaussian mixture models
Multivariate regression with compositional data

Multivariate regression with compositional data
Empirical likelihood hypothesis testing for two mean vectors

Empirical likelihood hypothesis testing for two mean vectors
Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions

Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions
Tuning the value of alpha in the alpha-regression

Tuning the value of \(\alpha\) in the \(\alpha\)-regression
Fitting a Dirichlet distribution

Fitting a Dirichlet distribution
Hotelling's multivariate version of the 2 sample t-test for Euclidean data

Hotelling's multivariate version of the 2 sample t-test for Euclidean data
Principal components regression

Principal components regression
Hotelling's multivariate version of the 1 sample t-test for Euclidean data

Hotelling's multivariate version of the 1 sample t-test for Euclidean data
Log-likelihood ratio test for a Dirichlet mean vector

Log-likelihood ratio test for a Dirichlet mean vector
Fitting a Dirichlet distribution via Newton-Rapshon

Fitting a Dirichlet distribution via Newton-Rapshon
Empirical likelihood for a one sample mean vector hypothesis testing

Empirical likelihood for a one sample mean vector hypothesis testing
Multivariate normal random values simulation on the simplex

Multivariate normal random values simulation on the simplex
Tuning of the k-NN algorithm for compositional data

Tuning of the he k-NN algorithm for compositional data
Multivariate skew normal random values simulation on the simplex

Multivariate skew normal random values simulation on the simplex
Contour plot of the skew skew-normal distribution in S^2

Contour plot of the skew skew-normal distribution in \(S^2\)
Multivariate t random values simulation on the simplex

Multivariate t random values simulation on the simplex
Estimating location and scatter parameters for compositional data

Estimating location and scatter parameters for compositional data
Regularised discriminant analysis for Euclidean data

Regularised discriminant analysis for Euclidean data
Contour plot of the kernel density estimate in S^2

Contour plot of the kernel density estimate in \(S^2\)
Ternary diagram

Ternary diagram
Log-likelihood ratio test for a symmetric Dirichlet distribution

Log-likelihood ratio test for a symmetric Dirichlet distribution
Exponential empirical likelihood for a one sample mean vector hypothesis testing

Exponential empirical likelihood for a one sample mean vector hypothesis testing
Multivariate linear regression

Multivariate linear regression
Multivariate analysis of variance

Multivariate analysis of variance
Multivariate analysis of variance (James test)

Multivariate analysis of variance (James test)
Exponential empirical likelihood hypothesis testing for two mean vectors

Exponential empirical likelihood hypothesis testing for two mean vectors
Contour plot of a Dirichlet distribution in S^2

Contour plot of a Dirichlet distribution in \(S^2\)
Tuning the principal components with GLMs

Tuning the principal components with GLMs
MLE for the multivarite t distribution

MLE for the multivarite t distribution
Ridge regression

Ridge regression
Cross validation for the ridge regression

Cross validation for the ridge regression
Spatial median regression

Spatial median regression
The Helmert sub-matrix

The Helmert sub-matrix
Spatial sign covariance matrix

Spatial sign covariance matrix
Principal component generalised linear models

Principal component generalised linear models
The Frechet mean for compositional data

The Frechet mean for compositional data
Total variability

Total variability
Gaussian mixture models for compositional data

Gaussian mixture models for compositional data
Contour plot of a Gaussian mixture model in S^2

Contour plot of a Gaussian mixture model in \(S^2\)
Non linear least squares regression for compositional data

Non linear least squares regression for compositional data
Contour plot of the normal distribution in S^2

Contour plot of the normal distribution in \(S^2\)
Tuning the parameters of the regularised discriminant analysis

Tuning the parameters of the regularised discriminant analysis
Zero adjusted Dirichlet regression

Zero adjusted Dirichlet regression
Dirichlet random values simulation

Dirichlet random values simulation
James multivariate version of the t-test

James multivariate version of the t-test
Divergence based regression for compositional data

Divergence based regression for compositional data
Multivariate kernel density estimation

Multivariate kernel density estimation
Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation

Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation
Ridge regression plot

Ridge regression plot
Simulation of compositional data from the folded model

Simulation of compositional data from the folded model
Regression with compositional data using the alpha-transformation

Regression with compositional data using the \(\alpha\)-transformation
The alpha-distance

The \(\alpha\)-distance
Compositional-package

Compositional Data Analysis
Regularised discriminant analysis for compositional data using the alpha-transformation

Regularised discriminant analysis for compositional data using the \(\alpha\)-transformation
Ridge regression with compositional data in the covariates side using the alpha-transformation

Ridge regression with compositional data in the covariates side using the \(\alpha\)-transformation
Estimation of the value of alpha via the profile log-likelihood

Estimation of the value of \(\alpha\) via the alfa profile log-likelihood
The alpha-transformation

The \(\alpha\)-transformation
Estimation of the value of alpha in the folded model

Estimation of the value of \(\alpha\) in the folded model
MLE of the folded model for a given value of alpha

MLE of the folded model for a given value of \(\alpha\)
Fast estimation of the value of alpha

Fast estimation of the value of \(\alpha\)
Multivariate or univariate regression with compositional data in the covariates side using the alpha-transformation

Multivariate or univariate regression with compositional data in the covariates side using the \(\alpha\)-transformation
Mixture model selection via BIC

Mixture model selection via BIC
Cross validation for the ridge regression with compositional data as predictor using the alpha-transformation

Cross validation for the ridge regression with compositional data as predictor using the \(\alpha\)-transformation
Contour plot of the t distribution in S^2

Contour plot of the t distribution in \(S^2\)
Cross validation for the regularised discriminant analysis with compositional data using the alpha-transformation

Cross validation for the regularised discriminant analysis with compositional data using the \(\alpha\)-transformation
Inverse of the alpha-transformation

Inverse of the \(\alpha\)-transformation
The additive log-ratio transformation and its inverse

The additive log-ratio transformation and its inverse
Tuning the number of PCs in the PCR with compositional data using the alpha-transformation

Tuning the number of PCs in the PCR with compositional data using the \(\alpha\)-transformation