Compositional package - RDocumentation

Hypothesis testing for two or more compositional mean vectors

bMixture model selection via BIC

Mixture model selection via BIC

Regularised discriminant analysis for compositional data using the alpha-transformation

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

Contour plot of the kernel density estimate in S^2

Contour plot of the kernel density estimate in $S^2$

Estimating location and scatter parameters for compositional data

Ridge regression with the alpha-transformation plot

Ridge regression plot

The k-NN algorithm for compositional data

Multivariate regression with compositional data

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

Contour plot of the t distribution in S^2

Contour plot of the t distribution in $S^2$

Tuning of the k-NN algorithm for compositional data

Tuning of the he k-NN algorithm for compositional data

Dirichlet regression

Compositional-package

Compositional Data Analysis

Exponential empirical likelihood for a one sample mean vector hypothesis testing

Density values of a Dirichlet distribution

Contour plot of a Dirichlet distribution in S^2

Contour plot of a Dirichlet distribution in $S^2$

Fitting a Dirichlet distribution via Newton-Rapshon

Exponential empirical likelihood hypothesis testing for two mean vectors

Fitting a Dirichlet distribution

Log-likelihood ratio test for a Dirichlet mean vector

Empirical likelihood for a one sample mean vector hypothesis testing

Divergence based regression for compositional data

Hotelling's multivariate version of the t-test

Principal component generalised linear models

Tuning the principal components with GLMs

Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions

hotel1T2

Hotelling's multivariate version of the t-test

The Helmert sub-matrix

Empirical likelihood hypothesis testing for two mean vectors

James multivariate version of the t-test

Multivariate analysis of variance

Gaussian mixture models for compositional data

Contour plot of a Gaussian mixture model in S^2

Contour plot of a Gaussian mixture model in $S^2$

Contour plot of the normal distribution in S^2

Contour plot of the normal distribution in $S^2$

Non linear least squares regression for compositional data

Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation

Multivariate analysis of variance (James test)

Multivariate kernel density estimation

Multivariate linear regression

MLE for the multivarite t distribution

Multivariate t random values simulation on the simplex

Regularised discriminant analysis for Euclidean data

Tuning of the principal components regression

Principal components regression

Ridge regression

Ridge regression plot

Tuning the parameters of the regularised discriminant analysis

Multivariate skew normal random values simulation on the simplex

Multivariate normal random values simulation on the simplex

Dirichlet random values simulation

Contour plot of the skew skewnormal distribution in S^2

Contour plot of the skew skewnormal distribution in $S^2$

Ternary diagram

Log-likelihood ratio test for a symmetric Dirichlet distribution

Spatial median for Euclidean data

Cross validation for the ridge regression

Spatial sign covariance matrix

Spatial median regression

Multivariate t random values simulation

Multivariate normal random values simulation

Simulation of compositional data from Gaussian mixture models

Compositional (version 2.0)

Compositional Data Analysis

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Functions in Compositional (2.0)