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| Compositional-package | Compositional Data Analysis |
| a.est | Estimation of the value of alpha in the folded model |
| a.mle | MLE of the folded model for a given value of alpha |
| alef | The alpha-transformation |
| alfa | The alpha-transformation |
| alfa.knn | The k-NN algorithm for compositional data |
| alfa.pcr | Multivariate or univariate regression with compositional data in the covariates side using the alpha-transformation |
| alfa.profile | Estimation of the value of alpha via the alfa profile log-likelihood |
| alfa.rda | Regularised discriminant analysis for compositional data using the alpha-transformation |
| alfa.reg | Regression with compositional data using the alpha-transformation |
| alfa.ridge | Ridge regression with compositional data in the covariates side using the alpha-transformation |
| alfa.tune | Fast estimation of the value of alpha |
| alfadist | The alpha-distance |
| alfadista | The alpha-distance |
| alfainv | Inverse of the alpha-transformation |
| alfaknn.tune | Tuning of the he k-NN algorithm for compositional data |
| alfapcr.tune | Tuning the number of PCs in the PCR with compositional data using the alpha-transformation |
| alfarda.tune | Cross validation for the regularised discriminant analysis with compositional data using the alpha-transformation |
| alfareg.tune | Tuning the value of alpha in the alpha-regression |
| alfaridge.plot | Ridge regression plot |
| alfaridge.tune | Cross validation for the ridge regression with compositional data as predictor using the alpha-transformation |
| alpha.mle | MLE of the folded model for a given value of alpha |
| alr | The additive log-ratio transformation and its inverse |
| alrinv | The additive log-ratio transformation and its inverse |
| bic.mixcompnorm | Mixture model selection via BIC |
| bivt.contour | Contour plot of the t distribution in S^2 |
| comp.den | Estimating location and scatter parameters for compositional data |
| comp.kerncontour | Contour plot of the kernel density estimate in S^2 |
| comp.knn | The k-NN algorithm for compositional data |
| comp.reg | Multivariate regression with compositional data |
| comp.test | Hypothesis testing for two or more compositional mean vectors |
| compknn.tune | Tuning of the he k-NN algorithm for compositional data |
| ddiri | Density values of a Dirichlet distribution |
| diri.contour | Contour plot of a Dirichlet distribution in S^2 |
| diri.est | Fitting a Dirichlet distribution |
| diri.nr | Fitting a Dirichlet distribution via Newton-Rapshon |
| diri.reg | Dirichlet regression |
| diri.reg2 | Dirichlet regression |
| dirimean.test | Log-likelihood ratio test for a Dirichlet mean vector |
| eel.test1 | Exponential empirical likelihood for a one sample mean vector hypothesis testing |
| eel.test2 | Exponential empirical likelihood hypothesis testing for two mean vectors |
| el.test1 | Empirical likelihood for a one sample mean vector hypothesis testing |
| el.test2 | Empirical likelihood hypothesis testing for two mean vectors |
| frechet | The Frechet mean for compositional data |
| glm.pcr | Principal component generalised linear models |
| glmpcr.tune | Tuning the principal components with GLMs |
| helm | The Helmert sub-matrix |
| hotel1T2 | Hotelling's multivariate version of the 1 sample t-test for Euclidean data |
| hotel2T2 | Hotelling's multivariate version of the 2 sample t-test for Euclidean data |
| james | James multivariate version of the t-test |
| js.compreg | Divergence based regression for compositional data |
| kl.compreg | Divergence based regression for compositional data |
| kl.compreg2 | Helper functions for the Kullback-Leibler regression |
| kl.diri | Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions |
| klcompreg.boot | Helper functions for the Kullback-Leibler regression |
| maov | Multivariate analysis of variance |
| maovjames | Multivariate analysis of variance (James test) |
| mix.compnorm | Gaussian mixture models for compositional data |
| mixnorm.contour | Contour plot of a Gaussian mixture model in S^2 |
| mixreg | Zero adjusted Dirichlet regression |
| mkde | Multivariate kernel density estimation |
| mkde.tune | Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation |
| multinompcr.tune | Tuning the principal components with GLMs |
| multivreg | Multivariate linear regression |
| multivt | MLE for the multivarite t distribution |
| norm.contour | Contour plot of the normal distribution in S^2 |
| ols.compreg | Non linear least squares regression for compositional data |
| pcr | Principal components regression |
| pcr.tune | Tuning of the principal components regression |
| rcompnorm | Multivariate normal random values simulation on the simplex |
| rcompsn | Multivariate skew normal random values simulation on the simplex |
| rcompt | Multivariate t random values simulation on the simplex |
| rda | Regularised discriminant analysis for Euclidean data |
| rda.tune | Tuning the parameters of the regularised discriminant analysis |
| rdiri | Dirichlet random values simulation |
| rfolded | Simulation of compositional data from the folded model |
| ridge.plot | Ridge regression plot |
| ridge.reg | Ridge regression |
| ridge.tune | Cross validation for the ridge regression |
| rmixcomp | Simulation of compositional data from Gaussian mixture models |
| skewnorm.contour | Contour plot of the skew skew-normal distribution in S^2 |
| spatmed.reg | Spatial median regression |
| sscov | Spatial sign covariance matrix |
| sym.test | Log-likelihood ratio test for a symmetric Dirichlet distribution |
| ternary | Ternary diagram |
| totvar | Total variability |
| zadr | Zero adjusted Dirichlet regression |