Compositional package - RDocumentation

bMixture model selection via BIC

Mixture model selection via BIC

Multivariate regression with compositional data

The k-NN algorithm for compositional data

Hypothesis testing for two or more compositional mean vectors

Regularised discriminant analysis for compositional data using the alpha-transformation

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

Ridge regression with the alpha-transformation plot

Ridge regression plot

Contour plot of the t distribution in S^2

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

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

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

Compositional-package

Compositional Data Analysis

Log-likelihood ratio test for a Dirichlet mean vector

Dirichlet regression

Exponential empirical likelihood for a one sample mean vector hypothesis testing

Contour plot of a Dirichlet distribution in S^2

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

Fitting a Dirichlet distribution

Fitting a Dirichlet distribution via Newton-Rapshon

Tuning of the k-NN algorithm for compositional data

Tuning of the he k-NN algorithm for compositional data

Density values of a Dirichlet distribution

Exponential empirical likelihood hypothesis testing for two mean vectors

Hotelling's multivariate version of the t-test

The Helmert sub-matrix

Tuning the principal components with GLMs

James multivariate version of the t-test

Empirical likelihood hypothesis testing for two mean vectors

hotel1T2

Hotelling's multivariate version of the t-test

Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions

Divergence based regression for compositional data

Empirical likelihood for a one sample mean vector hypothesis testing

Principal component generalised linear models

MLE for the multivarite t distribution

Multivariate analysis of variance (James test)

Non linear least squares regression for compositional data

Multivariate linear regression

Gaussian mixture models for compositional data

Contour plot of a Gaussian mixture model in S^2

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

Multivariate kernel density estimation

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

Multivariate analysis of variance

Contour plot of the normal distribution in S^2

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

Tuning of the principal components regression

Tuning the parameters of the regularised discriminant analysis

Dirichlet random values simulation

Multivariate skew normal random values simulation on the simplex

Multivariate normal random values simulation on the simplex

Ridge regression plot

Ridge regression

Principal components regression

Multivariate t random values simulation on the simplex

Regularised discriminant analysis for Euclidean data

Multivariate t random values simulation

Multivariate normal random values simulation

Spatial sign covariance matrix

Spatial median regression

Ternary diagram

Log-likelihood ratio test for a symmetric Dirichlet distribution

Contour plot of the skew skewnormal distribution in S^2

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

Simulation of compositional data from Gaussian mixture models

Cross validation for the ridge regression

Spatial median for Euclidean data

Compositional (version 1.6)

Compositional Data Analysis

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Functions in Compositional (1.6)