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Compositional (version 2.6)
Compositional Data Analysis
Description
Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included.
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Install
install.packages('Compositional')
Monthly Downloads
1,482
Version
2.6
License
GPL (>= 2)
Maintainer
Michail Tsagris
Last Published
October 7th, 2017
Functions in Compositional (2.6)
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The alpha-distance
The \(\alpha\)-distance
Inverse of the alpha-transformation
Inverse of the \(\alpha\)-transformation
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
Estimation of the value of alpha via the profile log-likelihood
Estimation of the value of \(\alpha\) via the alfa profile log-likelihood
Regularised discriminant analysis for compositional data using the alpha-transformation
Regularised discriminant analysis for compositional data using the \(\alpha\)-transformation
Regression with compositional data using the alpha-transformation
Regression with compositional data using the \(\alpha\)-transformation
Compositional-package
Compositional Data Analysis
The alpha-transformation
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
Fast estimation of the value of alpha
Fast estimation of the value of \(\alpha\)
Estimating location and scatter parameters for compositional data
Estimating location and scatter parameters for compositional data
Contour plot of the kernel density estimate in S^2
Contour plot of the kernel density estimate in \(S^2\)
Dirichlet regression
Dirichlet regression
Log-likelihood ratio test for a Dirichlet mean vector
Log-likelihood ratio test for a Dirichlet mean vector
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
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
The k-NN algorithm for compositional data
The 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
Multivariate analysis of variance
Multivariate analysis of variance
Multivariate analysis of variance (James test)
Multivariate analysis of variance (James test)
Multivariate normal random values simulation on the simplex
Multivariate normal random values simulation on the simplex
Multivariate skew normal random values simulation on the simplex
Multivariate skew normal random values simulation on the simplex
Ridge regression plot
Ridge regression plot
Mixture model selection via BIC
Mixture model selection via BIC
Contour plot of the t distribution in S^2
Contour plot of the t distribution in \(S^2\)
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
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
Density values of a Dirichlet distribution
Density values of a Dirichlet distribution
Contour plot of a Dirichlet distribution in S^2
Contour plot of a Dirichlet distribution in \(S^2\)
Tuning the value of alpha in the alpha-regression
Tuning the value of \(\alpha\) in the \(\alpha\)-regression
Ridge regression with the alpha-transformation plot
Ridge regression plot
Fitting a Dirichlet distribution
Fitting a Dirichlet distribution
The Frechet mean for compositional data
The Frechet mean for compositional data
Principal component generalised linear models
Principal component generalised linear models
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
Multivariate linear regression
Multivariate linear regression
MLE for the multivarite t distribution
MLE for the multivarite t distribution
Spatial sign covariance matrix
Spatial sign covariance matrix
Log-likelihood ratio test for a symmetric Dirichlet distribution
Log-likelihood ratio test for a symmetric Dirichlet distribution
Ridge regression
Ridge regression
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
Empirical likelihood hypothesis testing for two mean vectors
Empirical likelihood hypothesis testing for two mean vectors
Helper functions for the Kullback-Leibler regression
Helper functions for the Kullback-Leibler regression
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
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 \(S^2\)
Principal components regression
Principal components regression
Tuning of the principal components regression
Tuning of the principal components regression
Cross validation for the ridge regression
Cross validation for the ridge regression
Simulation of compositional data from Gaussian mixture models
Simulation of compositional data from Gaussian mixture models
Multivariate t random values simulation on the simplex
Multivariate t random values simulation on the simplex
Regularised discriminant analysis for Euclidean data
Regularised discriminant analysis for Euclidean data
Contour plot of the skew skewnormal distribution in S^2
Contour plot of the skew skewnormal distribution in \(S^2\)
The Helmert sub-matrix
The Helmert sub-matrix
Spatial median regression
Spatial median regression
Multivariate regression with compositional data
Multivariate regression with compositional data
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
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
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
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
Non linear least squares regression for compositional data
Tuning the parameters of the regularised discriminant analysis
Tuning the parameters of the regularised discriminant analysis
Dirichlet random values simulation
Dirichlet random values simulation
Ternary diagram
Ternary diagram