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Compositional (version 2.2)
Compositional Data Analysis
Description
A collection of functions for compositional data analysis.
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Install
install.packages('Compositional')
Monthly Downloads
1,183
Version
2.2
License
GPL (>= 2)
Maintainer
Michail Tsagris
Last Published
December 13th, 2016
Functions in Compositional (2.2)
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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 $S^2$
Multivariate regression with compositional data
Multivariate regression with compositional data
Contour plot of the kernel density estimate in S^2
Contour plot of the kernel density estimate in $S^2$
Hypothesis testing for two or more compositional mean vectors
Hypothesis testing for two or more compositional mean vectors
The k-NN algorithm for compositional data
The k-NN algorithm 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
Estimating location and scatter parameters for compositional data
Estimating location and scatter parameters for compositional data
Mixture model selection via BIC
Mixture model selection via BIC
Compositional-package
Compositional Data Analysis
Tuning of the k-NN algorithm for compositional data
Tuning of the he k-NN algorithm for compositional data
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
Log-likelihood ratio test for a Dirichlet mean vector
Log-likelihood ratio test for a Dirichlet mean vector
Dirichlet regression
Dirichlet regression
Fitting a Dirichlet distribution via Newton-Rapshon
Fitting a Dirichlet distribution via Newton-Rapshon
Fitting a Dirichlet distribution
Fitting a Dirichlet distribution
Contour plot of a Dirichlet distribution in S^2
Contour plot of a Dirichlet distribution in $S^2$
Density values of a Dirichlet distribution
Density values of a Dirichlet distribution
Principal component generalised linear models
Principal component generalised linear models
Tuning the principal components with GLMs
Tuning the principal components with GLMs
Divergence based regression for compositional data
Divergence based regression for compositional data
Empirical likelihood for a one sample mean vector hypothesis testing
Empirical likelihood for a one sample mean vector hypothesis testing
Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions
Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions
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
Empirical likelihood hypothesis testing for two mean vectors
Empirical likelihood hypothesis testing for two mean vectors
James multivariate version of the t-test
James multivariate version of the t-test
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
The Helmert sub-matrix
The Helmert sub-matrix
Multivariate analysis of variance
Multivariate analysis of variance
Multivariate kernel density estimation
Multivariate kernel density estimation
Multivariate analysis of variance (James test)
Multivariate analysis of variance (James test)
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
Multivariate linear regression
Multivariate linear regression
MLE for the multivarite t distribution
MLE for the multivarite t distribution
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 $S^2$
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 $S^2$
Multivariate t random values simulation on the simplex
Multivariate t random values simulation on the simplex
Multivariate skew normal random values simulation on the simplex
Multivariate skew normal random values simulation on the simplex
Principal components regression
Principal components regression
Multivariate normal random values simulation on the simplex
Multivariate normal random values simulation on the simplex
Regularised discriminant analysis for Euclidean data
Regularised discriminant analysis for Euclidean data
Tuning of the principal components regression
Tuning of the principal components regression
Ridge regression plot
Ridge regression plot
Tuning the parameters of the regularised discriminant analysis
Tuning the parameters of the regularised discriminant analysis
Ridge regression
Ridge regression
Dirichlet random values simulation
Dirichlet random values simulation
Spatial sign covariance matrix
Spatial sign covariance matrix
Spatial median regression
Spatial median regression
Spatial median for Euclidean data
Spatial median for Euclidean data
Contour plot of the skew skewnormal distribution in S^2
Contour plot of the skew skewnormal distribution in $S^2$
Log-likelihood ratio test for a symmetric Dirichlet distribution
Log-likelihood ratio test for a symmetric Dirichlet distribution
Simulation of compositional data from Gaussian mixture models
Simulation of compositional data from Gaussian mixture models
Cross validation for the ridge regression
Cross validation for the ridge regression
Ternary diagram
Ternary diagram