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Compositional (version 2.9)

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.

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Version

Install

install.packages('Compositional')

Monthly Downloads

1,059

Version

2.9

License

GPL (>= 2)

Maintainer

Michail Tsagris

Last Published

March 7th, 2018

Functions in Compositional (2.9)

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
Ridge regression with the alpha-transformation plot

Ridge regression plot
Mixture model selection via BIC

Mixture model selection via BIC
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
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
The additive log-ratio transformation and its inverse

The additive log-ratio transformation and its inverse
Contour plot of the t distribution in S^2

Contour plot of the t distribution in \(S^2\)
MLE of the folded model for a given value of alpha

MLE of the folded model for a given value of \(\alpha\)
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
Inverse of the alpha-transformation

Inverse of the \(\alpha\)-transformation
Hypothesis testing for two or more compositional mean vectors

Hypothesis testing for two or more compositional mean vectors
Tuning of the k-NN algorithm for compositional data

Tuning of the he k-NN algorithm for compositional data
The Frechet mean for compositional data

The Frechet mean for compositional data
Principal component generalised linear models

Principal component generalised linear models
The k-NN algorithm for compositional data

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

Density values of a Dirichlet distribution
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
Estimating location and scatter parameters for compositional data

Estimating location and scatter parameters for compositional data
Contour plot of a Dirichlet distribution in S^2

Contour plot of a Dirichlet distribution in \(S^2\)
Helper functions for the Kullback-Leibler regression

Helper functions for the Kullback-Leibler regression
Contour plot of the kernel density estimate in S^2

Contour plot of the kernel density estimate in \(S^2\)
Multivariate regression with compositional data

Multivariate regression with compositional data
Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions

Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions
Tuning the principal components with GLMs

Tuning the principal components with GLMs
Log-likelihood ratio test for a Dirichlet mean vector

Log-likelihood ratio test for a Dirichlet mean vector
Tuning the value of alpha in the alpha-regression

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

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

Exponential empirical likelihood for a one sample mean vector hypothesis testing
Exponential empirical likelihood hypothesis testing for two mean vectors

Exponential empirical likelihood hypothesis testing for two mean vectors
The Helmert sub-matrix

The Helmert sub-matrix
Multivariate analysis of variance

Multivariate analysis of variance
Principal components regression

Principal components regression
Tuning of the principal components regression

Tuning of the 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
James multivariate version of the t-test

James multivariate version of the t-test
Multivariate analysis of variance (James test)

Multivariate analysis of variance (James test)
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
Divergence based regression for compositional data

Divergence based regression for compositional data
Simulation of compositional data from Gaussian mixture models

Simulation of compositional data from Gaussian mixture models
Fitting a Dirichlet distribution

Fitting a Dirichlet distribution
Multivariate kernel density estimation

Multivariate kernel density estimation
Fitting a Dirichlet distribution via Newton-Rapshon

Fitting a Dirichlet distribution via Newton-Rapshon
Contour plot of the skew skew-normal distribution in S^2

Contour plot of the skew skew-normal distribution in \(S^2\)
Total variability

Total variability
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
Contour plot of the normal distribution in S^2

Contour plot of the normal distribution in \(S^2\)
Zero adjusted Dirichlet regression

Zero adjusted Dirichlet regression
Empirical likelihood for a one sample mean vector hypothesis testing

Empirical likelihood for a one sample mean vector hypothesis testing
Empirical likelihood hypothesis testing for two mean vectors

Empirical likelihood hypothesis testing for two mean vectors
Non linear least squares regression for compositional data

Non linear least squares regression for compositional data
Ridge regression

Ridge regression
Tuning the parameters of the regularised discriminant analysis

Tuning the parameters of the regularised discriminant analysis
Dirichlet random values simulation

Dirichlet random values simulation
Cross validation for the ridge regression

Cross validation for the ridge regression
Multivariate skew normal random values simulation on the simplex

Multivariate skew normal random values simulation on the simplex
Multivariate normal random values simulation on the simplex

Multivariate normal random values simulation on the simplex
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 \(S^2\)
Simulation of compositional data from the folded model

Simulation of compositional data from the folded model
Ridge regression plot

Ridge regression plot
Multivariate linear regression

Multivariate linear regression
Spatial median regression

Spatial median regression
Spatial sign covariance matrix

Spatial sign covariance matrix
MLE for the multivarite t distribution

MLE for the multivarite t distribution
Regularised discriminant analysis for Euclidean data

Regularised discriminant analysis for Euclidean data
Multivariate t random values simulation on the simplex

Multivariate t random values simulation on the simplex
Log-likelihood ratio test for a symmetric Dirichlet distribution

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

Ternary diagram
Estimation of the value of alpha via the profile log-likelihood

Estimation of the value of \(\alpha\) via the alfa profile log-likelihood
Estimation of the value of alpha in the folded model

Estimation of the value of \(\alpha\) in the folded model
Compositional-package

Compositional Data Analysis
Fast estimation of the value of alpha

Fast estimation of the value of \(\alpha\)
The alpha-distance

The \(\alpha\)-distance
The alpha-transformation

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

Regression with compositional data using the \(\alpha\)-transformation
Regularised discriminant analysis for compositional data using the alpha-transformation

Regularised discriminant analysis for compositional data using the \(\alpha\)-transformation