| 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 |
| acor |
alpha-generalised correlations between two compositional datasets |
| acor.tune |
Tuning of the alpha-generalised correlations between two compositional datasets |
| aeqdist.etest |
Energy test of equality of distributions using the alpha-transformation |
| ait |
The alpha-IT transformation |
| ait.knn |
The k-NN algorithm for compositional data |
| ait.test |
Aitchison's test for two mean vectors and/or covariance matrices |
| aitdist |
The alpha-IT-distance |
| aitdista |
The alpha-IT-distance |
| aitknn.tune |
Tuning of the k-NN algorithm for compositional data |
| akern.reg |
The alpha-kernel regression with compositional response data |
| akernreg.tune |
Cross validation for the alpha-kernel regression with compositional response data |
| aknn.reg |
The alpha-k-NN regression for compositional response data |
| aknnreg.tune |
Cross validation for the alpha-k-NN regression with compositional response data |
| alef |
The alpha-transformation |
| alfa |
The alpha-transformation |
| alfa.contour |
Contour plot of the alpha multivariate normal in S^2 |
| alfa.fda |
Regularised and flexible discriminant analysis for compositional data using the alpha-transformation |
| alfa.knn |
The k-NN algorithm for compositional data |
| alfa.knn.reg |
The alpha-k-NN regression with compositional predictor variables |
| alfa.lasso |
LASSO with compositional predictors using the alpha-transformation |
| alfa.mds |
Principal coordinate analysis using the alpha-distance |
| alfa.mix.norm |
Gaussian mixture models for compositional data using the alpha-transformation |
| alfa.nb |
Naive Bayes classifiers for compositional data using the alpha-transformation |
| alfa.pca |
Principal component analysis using the alpha-transformation |
| alfa.pcr |
Multivariate or univariate regression with compositional data in the covariates side using the alpha-transformation |
| alfa.pprcomp |
Projection pursuit regression with compositional predictor variables using the alpha-transformation |
| alfa.profile |
Estimation of the value of alpha via the alfa profile log-likelihood |
| alfa.rda |
Regularised and flexible discriminant analysis for compositional data using the alpha-transformation |
| alfa.reg |
Regression with compositional data using the alpha-transformation |
| alfa.reg2 |
Regression with compositional data using the alpha-transformation |
| alfa.reg3 |
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 |
| alfafda.tune |
Cross validation for the regularised and flexible discriminant analysis with compositional data using the alpha-transformation |
| alfainv |
Inverse of the alpha-transformation |
| alfaknn.tune |
Tuning of the k-NN algorithm for compositional data |
| alfaknnreg.tune |
Cross validation for the alpha-k-NN regression with compositional predictor variables |
| alfalasso.tune |
Cross-validation for LASSO with compositional predictors using the alpha-transformation |
| alfanb.tune |
Cross-validation for the naive Bayes classifiers for compositional data using the alpha-transformation |
| alfann |
The k-nearest neighbours using the alpha-distance |
| alfapcr.tune |
Tuning the number of PCs in the PCR with compositional data using the alpha-transformation |
| alfapprcomp.tune |
Tuning of the projection pursuit regression with compositional predictor variables using the alpha-transformation |
| alfarda.tune |
Cross validation for the regularised and flexible 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 |
| alr.all |
All pairwise additive log-ratio transformations |
| alrinv |
The additive log-ratio transformation and its inverse |
| ascls |
The alpha-SCLS model for compositional responses and predictors |
| atflr |
The alpha-TFLR model for compositional responses and predictors |
| colbeta.est |
Column-wise MLE of some univariate distributions |
| collogitnorm.est |
Column-wise MLE of some univariate distributions |
| colunitweibull.est |
Column-wise MLE of some univariate distributions |
| colzilogitnorm.est |
Column-wise MLE of some univariate distributions |
| comp.den |
Estimating location and scatter parameters for compositional data |
| comp.kern |
Multivariate kernel density estimation 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.nb |
Naive Bayes classifiers for compositional data |
| comp.ppr |
Projection pursuit regression 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 k-NN algorithm for compositional data |
| compnorm.contour |
Contour plot of the normal distribution in S^2 |
| compppr.tune |
Tuning of the projection pursuit regression for compositional data |
| cv.ascls |
Cross-validation for the alpha-SCLS model |
| cv.atflr |
Cross-validation for the alpha-TFLR model |
| cv.comp.reg |
Cross validation for some compositional regression models |
| cv.compnb |
Cross-validation for the naive Bayes classifiers for compositional data |
| cv.dda |
Cross-validation for the Dirichlet discriminant analysis |
| cv.lasso.compreg |
Cross-validation for the LASSO log-ratio regression with compositional response |
| cv.lasso.klcompreg |
Cross-validation for the LASSO Kullback-Leibler divergence based regression |
| cv.scls |
Cross-validation for the SCLS model |
| cv.scrq |
Cross-validation for the SCRQ model |
| cv.tflr |
Cross validation for the TFLR model |
| dda |
Dirichlet discriminant analysis |
| ddiri |
Density values of a Dirichlet distribution |
| dfd |
Density of the Flexible Dirichlet distribution |
| dfolded |
Density of the folded model normal distribution |
| dgendiri |
Density values of a generalised Dirichlet distribution |
| diri.contour |
Contour plot of the Dirichlet distribution in S^2 |
| diri.est |
MLE of the a Dirichlet distribution |
| diri.nr |
MLE of the Dirichlet distribution via Newton-Rapshon |
| diri.reg |
Dirichlet regression |
| diri.reg2 |
Dirichlet regression |
| diri.reg3 |
Dirichlet regression |
| dirimean.test |
Log-likelihood ratio test for a Dirichlet mean vector |
| divergence |
Divergence matrix of compositional data |
| dmix.compnorm |
Simulation of compositional data from Gaussian mixture models |
| dmixdiri |
Density values of a mixture of Dirichlet distributions |
| dptest |
Projections based test for distributional equality of two groups |
| kern.reg |
Kernel regression with a numerical response vector or matrix |
| kernreg.tune |
Cross validation for the kernel regression with Euclidean response data |
| kl.alfapcr |
Divergence based regression for compositional data with compositional data in the covariates side using the alpha-transformation |
| 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 |
| kl.diri.normal |
Minimized Kullback-Leibler divergence between Dirichlet and logistic normal |
| klalfapcr.tune |
Tuning of the divergence based regression for compositional data with compositional data in the covariates side using the alpha-transformation |
| klcompreg.boot |
Helper functions for the Kullback-Leibler regression |
| kumar.est |
MLE of distributions defined in the (0, 1) interval |
| lasso.compreg |
LASSO log-ratio regression with compositional response |
| lasso.klcompreg |
LASSO Kullback-Leibler divergence based regression |
| lassocoef.plot |
Plot of the LASSO coefficients |
| lc.glm |
Log-contrast GLMS with compositional predictor variables |
| lc.glm2 |
Log-contrast logistic or Poisson regression with with multiple compositional predictors |
| lc.reg |
Log-contrast regression with compositional predictor variables |
| lc.reg2 |
Log-contrast regression with multiple compositional predictors |
| lc.rq |
Log-contrast quantile regression with compositional predictor variables |
| lc.rq2 |
Log-contrast quantile regression with with multiple compositional predictors |
| lcglm.aov |
ANOVA for the log-contrast GLM versus the uncostrained GLM |
| lcreg.aov |
ANOVA for the log-contrast regression versus the uncostrained linear regression |
| logitnorm.est |
MLE of distributions defined in the (0, 1) interval |
| logpca |
Principal component analysis |
| makefolds |
Generate random folds for cross-validation |
| maov |
Multivariate analysis of variance assuming equality of the covariance matrices |
| maovjames |
Multivariate analysis of variance (James test) |
| mix.compnorm |
Gaussian mixture models for compositional data |
| mix.compnorm.contour |
Contour plot of the Gaussian mixture model in S^2 |
| mixdiri.contour |
Contour plot of mixtures of Dirichlet distributions in S^2 |
| mkde |
Multivariate kernel density estimation |
| mkde.tune |
Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation |
| mlr |
The multiplicative log-ratio transformation and its inverse |
| mlrinv |
The multiplicative log-ratio transformation and its inverse |
| multinompcr.tune |
Tuning the principal components with GLMs |
| multivreg |
Multivariate linear regression |
| multivt |
MLE for the multivariate t distribution |
| rbeta1 |
Random values generation from some univariate distributions defined on the (0,1) interval |
| 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 |
| read.fbm |
Read a file as a Filebacked Big Matrix |
| rfd |
Simulation of compositional data from the Flexible Dirichlet distribution |
| rfolded |
Simulation of compositional data from the folded model normal distribution |
| rgendiri |
Generalised Dirichlet random values simulation |
| ridge.plot |
Ridge regression plot |
| ridge.reg |
Ridge regression |
| ridge.tune |
Cross validation for the ridge regression |
| rlogitnorm |
Random values generation from some univariate distributions defined on the (0,1) interval |
| rmixcomp |
Simulation of compositional data from Gaussian mixture models |
| rmixdiri |
Simulation of compositional data from mixtures of Dirichlet distributions |
| runitweibull |
Random values generation from some univariate distributions defined on the (0,1) interval |