Package: Compositional 7.1

Michail Tsagris

Compositional: Compositional Data Analysis

Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. We further include functions for percentages (or proportions). The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include: a) Tsagris M.T., Preston S. and Wood A.T.A. (2011). "A data-based power transformation for compositional data". Fourth International International Workshop on Compositional Data Analysis. <doi:10.48550/arXiv.1106.1451> b) Tsagris M. (2014). "The k-NN algorithm for compositional data: a revised approach with and without zero values present". Journal of Data Science, 12(3): 519--534. <doi:10.6339/JDS.201407_12(3).0008>. c) Tsagris M. (2015). "A novel, divergence based, regression for compositional data". Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. <doi:10.48550/arXiv.1511.07600>. d) Tsagris M. (2015). "Regression analysis with compositional data containing zero values". Chilean Journal of Statistics, 6(2): 47--57. <https://soche.cl/chjs/volumes/06/02/Tsagris(2015).pdf>. e) Tsagris M., Preston S. and Wood A.T.A. (2016). "Improved supervised classification for compositional data using the alpha-transformation". Journal of Classification, 33(2): 243--261. <doi:10.1007/s00357-016-9207-5>. f) Tsagris M., Preston S. and Wood A.T.A. (2017). "Nonparametric hypothesis testing for equality of means on the simplex". Journal of Statistical Computation and Simulation, 87(2): 406--422. <doi:10.1080/00949655.2016.1216554>. g) Tsagris M. and Stewart C. (2018). "A Dirichlet regression model for compositional data with zeros". Lobachevskii Journal of Mathematics, 39(3): 398--412. <doi:10.1134/S1995080218030198>. h) Alenazi A. (2019). "Regression for compositional data with compositional data as predictor variables with or without zero values". Journal of Data Science, 17(1): 219--238. <doi:10.6339/JDS.201901_17(1).0010>. i) Tsagris M. and Stewart C. (2020). "A folded model for compositional data analysis". Australian and New Zealand Journal of Statistics, 62(2): 249--277. <doi:10.1111/anzs.12289>. j) Alenazi A. (2021). Alenazi, A. (2023). "A review of compositional data analysis and recent advances". Communications in Statistics--Theory and Methods, 52(16): 5535--5567. <doi:10.1080/03610926.2021.2014890>. k) Alenazi A.A. (2022). "f-divergence regression models for compositional data". Pakistan Journal of Statistics and Operation Research, 18(4): 867--882. <doi:10.18187/pjsor.v18i4.3969>. l) Tsagris M. and Stewart C. (2022). "A Review of Flexible Transformations for Modeling Compositional Data". In Advances and Innovations in Statistics and Data Science, pp. 225--234. <doi:10.1007/978-3-031-08329-7_10>. m) Tsagris M., Alenazi A. and Stewart C. (2023). "Flexible non-parametric regression models for compositional response data with zeros". Statistics and Computing, 33(106). <doi:10.1007/s11222-023-10277-5>. n) Tsagris. M. (2024). "Constrained least squares simplicial-simplicial regression". <doi:10.48550/arXiv.2403.19835>.

Authors:Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb], Christos Adam [ctb]

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# Install 'Compositional' in R:

install.packages('Compositional', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.55 score 2 stars 4 packages 127 scripts 1.7k downloads 1 mentions 222 exports 76 dependencies

Last updated 28 days agofrom:c8e1288a41. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 10 2024
R-4.5-linux	OK	Oct 10 2024

Exports:a.est a.mle acor acor.tune aeqdist.etest ait ait.knn ait.test aitdist aitdista aitknn.tune akern.reg akernreg.tune aknn.reg aknnreg.tune alef alfa alfa.contour alfa.fda alfa.knn alfa.knn.reg alfa.lasso alfa.mds alfa.mix.norm alfa.nb alfa.pca alfa.pcr alfa.pprcomp alfa.profile alfa.rda alfa.reg alfa.reg2 alfa.reg3 alfa.ridge alfa.tune alfadist alfadista alfafda.tune alfainv alfaknn.tune alfaknnreg.tune alfalasso.tune alfanb.tune alfann alfapcr.tune alfapprcomp.tune alfarda.tune alfareg.tune alfaridge.plot alfaridge.tune alpha.mle alr alr.all alrinv ascls atflr bc beta.est beta.reg bic.alfamixnorm bic.mixcompnorm bivt.contour colbeta.est collogitnorm.est colunitweibull.est colzilogitnorm.est comp.den comp.kern comp.kerncontour comp.knn comp.nb comp.ppr comp.reg comp.test compknn.tune compnorm.contour compppr.tune cv.ascls cv.atflr cv.comp.reg cv.compnb cv.dda cv.lasso.compreg cv.lasso.klcompreg cv.scls cv.scrq cv.tflr dda ddiri dfd dfolded dgendiri diri.contour diri.est diri.nr diri.reg diri.reg2 diri.reg3 dirimean.test divergence dmix.compnorm dmixdiri dptest es esov esov.mds esova fd.contour folded.contour fp frechet frechet2 gendiri.contour glm.pcr glmpcr.tune green hd.meantest2 helling.prop.reg helm hsecant01.est ibeta.est ice.akernreg ice.aknnreg ice.kernreg ice.pprcomp js.compreg kern.reg kernreg.tune kl.alfapcr kl.compreg kl.compreg2 kl.diri kl.diri.normal klalfapcr.tune klcompreg.boot kumar.est lasso.compreg lasso.klcompreg lassocoef.plot lc.glm lc.glm2 lc.reg lc.reg2 lc.rq lc.rq2 lcglm.aov lcreg.aov logitnorm.est logpca makefolds mix.compnorm mix.compnorm.contour mixdiri.contour mkde mkde.tune mlr mlrinv multinompcr.tune multivreg multivt ols.compreg ols.prop.reg pcc pcr.tune perturbation pivot pivotinv pow pprcomp pprcomp.tune probout propreg propregs rbeta1 rcompnorm rcompsn rcompt rdiri read.fbm rfd rfolded rgendiri ridge.plot ridge.reg ridge.tune rlogitnorm rmixcomp rmixdiri runitweibull scls scls.betest scls.indeptest scls2 scrq skewnorm.contour spatmed.reg sym.test symkl.compreg ternary ternary.coef ternary.coefcr ternary.mcr ternary.reg tflr tflr.betest tflr.indeptest tflr2 totvar tv.compreg ulc.glm ulc.glm2 ulc.reg ulc.reg2 ulc.rq ulc.rq2 unitweib.reg unitweibull.est zad.est zadr zadr2 zeroreplace zilogitnorm.est

Dependencies:BH bigassertr bigparallelr bigstatsr bit boot class cli cluster codetools colorspace cowplot doParallel emplik energy fansi farver ff flock foreach ggplot2 glmnet glue gsl gtable isoband iterators labeling lattice lifecycle magrittr MASS Matrix MatrixModels mda mgcv minpack.lm mixture mnormt munsell mvhtests nlme nnet numDeriv parallelly pillar pkgconfig ps quadprog quantreg R6 RColorBrewer Rcpp RcppArmadillo RcppEigen RcppGSL RcppParallel RcppZiggurat regda Rfast Rfast2 RhpcBLASctl rlang rmio Rnanoflann RSpectra scales shape sn SparseM survival tibble utf8 vctrs viridisLite withr

Help page	Topics
Compositional Data Analysis	Compositional-package
Aitchison's test for two mean vectors and/or covariance matrices	ait.test
All pairwise additive log-ratio transformations	alr.all
alpha-generalised correlations between two compositional datasets	acor
ANOVA for the log-contrast GLM versus the uncostrained GLM	lcglm.aov
ANOVA for the log-contrast regression versus the uncostrained linear regression	lcreg.aov
Beta regression	beta.reg
Column-wise MLE of some univariate distributions	colbeta.est collogitnorm.est colunitweibull.est colzilogitnorm.est
Contour plot of mixtures of Dirichlet distributions in S^2	mixdiri.contour
Contour plot of the alpha multivariate normal in S^2	alfa.contour
Contour plot of the alpha-folded model in S^2	folded.contour
Contour plot of the Dirichlet distribution in S^2	diri.contour
Contour plot of the Flexible Dirichlet distribution in S^2	fd.contour
Contour plot of the Gaussian mixture model in S^2	mix.compnorm.contour
Contour plot of the generalised Dirichlet distribution in S^2	gendiri.contour
Contour plot of the kernel density estimate in S^2	comp.kerncontour
Contour plot of the normal distribution in S^2	compnorm.contour
Contour plot of the skew skew-normal distribution in S^2	skewnorm.contour
Contour plot of the t distribution in S^2	bivt.contour
Cross validation for some compositional regression models	cv.comp.reg
Cross validation for the alpha-k-NN regression with compositional predictor variables	alfaknnreg.tune
Cross validation for the alpha-k-NN regression with compositional response data	aknnreg.tune
Cross validation for the alpha-kernel regression with compositional response data	akernreg.tune
Cross validation for the kernel regression with Euclidean response data	kernreg.tune
Cross validation for the regularised and flexible discriminant analysis with compositional data using the alpha-transformation	alfafda.tune alfarda.tune
Cross validation for the ridge regression	ridge.tune
Cross validation for the ridge regression with compositional data as predictor using the alpha-transformation	alfaridge.tune
Cross validation for the TFLR model	cv.tflr
Cross-validation for LASSO with compositional predictors using the alpha-transformation	alfalasso.tune
Cross-validation for the alpha-SCLS model	cv.ascls
Cross-validation for the alpha-TFLR model	cv.atflr
Cross-validation for the Dirichlet discriminant analysis	cv.dda
Cross-validation for the LASSO Kullback-Leibler divergence based regression	cv.lasso.klcompreg
Cross-validation for the LASSO log-ratio regression with compositional response	cv.lasso.compreg
Cross-validation for the naive Bayes classifiers for compositional data	cv.compnb
Cross-validation for the naive Bayes classifiers for compositional data using the alpha-transformation	alfanb.tune
Cross-validation for the SCLS model	cv.scls
Cross-validation for the SCRQ model	cv.scrq
Simulation of compositional data from Gaussian mixture models	dmix.compnorm
Density of the Flexible Dirichlet distribution	dfd
Density of the folded model normal distribution	dfolded
Density values of a Dirichlet distribution	ddiri
Density values of a generalised Dirichlet distribution	dgendiri
Density values of a mixture of Dirichlet distributions	dmixdiri
Dirichlet discriminant analysis	dda
Dirichlet random values simulation	rdiri
Dirichlet regression	diri.reg diri.reg2 diri.reg3
Distance based regression models for proportions	helling.prop.reg ols.prop.reg
Divergence based regression for compositional data	js.compreg kl.compreg symkl.compreg tv.compreg
Divergence based regression for compositional data with compositional data in the covariates side using the alpha-transformation	kl.alfapcr
Divergence matrix of compositional data	divergence
Energy test of equality of distributions using the alpha-transformation	aeqdist.etest
Estimating location and scatter parameters for compositional data	comp.den
Estimation of the probability left outside the simplex when using the alpha-transformation	probout
Estimation of the value of alpha in the folded model	a.est
Estimation of the value of alpha via the alfa profile log-likelihood	alfa.profile
Fast estimation of the value of alpha	alfa.tune
Gaussian mixture models for compositional data	mix.compnorm
Gaussian mixture models for compositional data using the alpha-transformation	alfa.mix.norm
Generalised Dirichlet random values simulation	rgendiri
Generate random folds for cross-validation	makefolds
Greenacre's power transformation	green
Helper Frechet mean for compositional data	frechet2
Helper functions for the Kullback-Leibler regression	kl.compreg2 klcompreg.boot
Hypothesis testing for two or more compositional mean vectors	comp.test
ICE plot for projection pursuit regression with compositional predictor variables	ice.pprcomp
ICE plot for the alpha-k-NN regression	ice.aknnreg
ICE plot for the alpha-kernel regression	ice.akernreg
ICE plot for univariate kernel regression	ice.kernreg
Inverse of the alpha-transformation	alfainv
Kernel regression with a numerical response vector or matrix	kern.reg
Kullback-Leibler divergence and Bhattacharyya distance between two Dirichlet distributions	kl.diri
LASSO Kullback-Leibler divergence based regression	lasso.klcompreg
LASSO log-ratio regression with compositional response	lasso.compreg
LASSO with compositional predictors using the alpha-transformation	alfa.lasso
Log-contrast GLMS with compositional predictor variables	lc.glm
Log-contrast logistic or Poisson regression with with multiple compositional predictors	lc.glm2
Log-contrast quantile regression with compositional predictor variables	lc.rq
Log-contrast quantile regression with with multiple compositional predictors	lc.rq2
Log-contrast regression with compositional predictor variables	lc.reg
Log-contrast regression with multiple compositional predictors	lc.reg2
Log-likelihood ratio test for a Dirichlet mean vector	dirimean.test
Log-likelihood ratio test for a symmetric Dirichlet distribution	sym.test
Minimized Kullback-Leibler divergence between Dirichlet and logistic normal	kl.diri.normal
Mixture model selection via BIC	bic.mixcompnorm
Mixture model selection with the alpha-transformation using BIC	bic.alfamixnorm
MLE for the multivariate t distribution	multivt
MLE of distributions defined in the (0, 1) interval	beta.est hsecant01.est ibeta.est kumar.est logitnorm.est unitweibull.est zilogitnorm.est
MLE of the a Dirichlet distribution	diri.est
MLE of the Dirichlet distribution via Newton-Rapshon	diri.nr
MLE of the folded model for a given value of alpha	a.mle alpha.mle
MLE of the zero adjusted Dirichlet distribution	zad.est
Multivariate kernel density estimation	mkde
Multivariate kernel density estimation for compositional data	comp.kern
Multivariate linear regression	multivreg
Multivariate normal random values simulation on the simplex	rcompnorm
Multivariate or univariate regression with compositional data in the covariates side using the alpha-transformation	alfa.pcr
Multivariate regression with compositional data	comp.reg
Multivariate skew normal random values simulation on the simplex	rcompsn
Multivariate t random values simulation on the simplex	rcompt
Naive Bayes classifiers for compositional data	comp.nb
Naive Bayes classifiers for compositional data using the alpha-transformation	alfa.nb
Non linear least squares regression for compositional data	ols.compreg
Non-parametric zero replacement strategies	zeroreplace
Permutation linear independence test in the SCLS model	scls.indeptest
Permutation linear independence test in the TFLR model	tflr.indeptest
Permutation test for the matrix of coefficients in the SCLS model	scls.betest
Permutation test for the matrix of coefficients in the TFLR model	tflr.betest
Perturbation operation	perturbation
Plot of the LASSO coefficients	lassocoef.plot
Power operation	pow
Principal component analysis	logpca
Principal component analysis using the alpha-transformation	alfa.pca
Principal component generalised linear models	glm.pcr
Principal coordinate analysis using the alpha-distance	alfa.mds
Principal coordinate analysis using the Jensen-Shannon divergence	esov.mds
Projection pursuit regression for compositional data	comp.ppr
Projection pursuit regression with compositional predictor variables	pprcomp
Projection pursuit regression with compositional predictor variables using the alpha-transformation	alfa.pprcomp
Projections based test for distributional equality of two groups	dptest
Proportionality correlation coefficient matrix	pcc
Quasi binomial regression for proportions	propreg propregs
Random values generation from some univariate distributions defined on the (0,1) interval	rbeta1 rlogitnorm runitweibull
Read a file as a Filebacked Big Matrix	read.fbm
Regression with compositional data using the alpha-transformation	alfa.reg alfa.reg2 alfa.reg3
Regularised and flexible discriminant analysis for compositional data using the alpha-transformation	alfa.fda alfa.rda
Ridge regression	ridge.reg
Ridge regression plot	ridge.plot
Ridge regression with compositional data in the covariates side using the alpha-transformation	alfa.ridge
Ridge regression plot	alfaridge.plot
Simplicial constrained median regression for compositional responses and predictors	scrq
Simulation of compositional data from Gaussian mixture models	rmixcomp
Simulation of compositional data from mixtures of Dirichlet distributions	rmixdiri
Simulation of compositional data from the Flexible Dirichlet distribution	rfd
Simulation of compositional data from the folded model normal distribution	rfolded
Spatial median regression	spatmed.reg
Ternary diagram	ternary
Ternary diagram of regression models	ternary.reg
Ternary diagram with confidence region for the matrix of coefficients of the SCLS or the TFLR model	ternary.coefcr
Ternary diagram with confidence region for the mean	ternary.mcr
Ternary diagram with the coefficients of the simplicial-simplicial regression models	ternary.coef
The additive log-ratio transformation and its inverse	alr alrinv
The alpha-distance	alfadist alfadista
The alpha-IT transformation	ait
The alpha-IT-distance	aitdist aitdista
The alpha-k-NN regression for compositional response data	aknn.reg
The alpha-k-NN regression with compositional predictor variables	alfa.knn.reg
The alpha-kernel regression with compositional response data	akern.reg
The alpha-SCLS model for compositional responses and predictors	ascls
The alpha-TFLR model for compositional responses and predictors	atflr
The alpha-transformation	alef alfa
The Box-Cox transformation applied to ratios of components	bc
The ESOV-distance	es esov esova
The folded power transformation	fp
The Frechet mean for compositional data	frechet
The Helmert sub-matrix	helm
The k-nearest neighbours using the alpha-distance	alfann
The k-NN algorithm for compositional data	ait.knn alfa.knn comp.knn
The multiplicative log-ratio transformation and its inverse	mlr mlrinv
The pivot coordinate transformation and its inverse	pivot pivotinv
Simplicial constrained linear least squares (SCLS) for compositional responses and predictors	scls
The SCLS model with multiple compositional predictors	scls2
The TFLR model with multiple compositional predictors	tflr2
Transformation-free linear regression (TFLR) for compositional responses and predictors	tflr
Total variability	totvar
Tuning of the alpha-generalised correlations between two compositional datasets	acor.tune
Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation	mkde.tune
Tuning of the divergence based regression for compositional data with compositional data in the covariates side using the alpha-transformation	klalfapcr.tune
Tuning of the k-NN algorithm for compositional data	aitknn.tune alfaknn.tune compknn.tune
Tuning of the projection pursuit regression for compositional data	compppr.tune
Tuning of the projection pursuit regression with compositional predictor variables	pprcomp.tune
Tuning of the projection pursuit regression with compositional predictor variables using the alpha-transformation	alfapprcomp.tune
Tuning the number of PCs in the PCR with compositional data using the alpha-transformation	alfapcr.tune
Tuning the principal components with GLMs	glmpcr.tune multinompcr.tune pcr.tune
Tuning the value of alpha in the alpha-regression	alfareg.tune
Two-sample test of high-dimensional means for compositional data	hd.meantest2
Unconstrained GLMs with compositional predictor variables	ulc.glm
Unconstrained linear regression with compositional predictor variables	ulc.reg
Unconstrained linear regression with multiple compositional predictors	ulc.reg2
Unconstrained logistic or Poisson regression with multiple compositional predictors	ulc.glm2
Unconstrained quantile regression with compositional predictor variables	ulc.rq
Unconstrained quantile regression with multiple compositional predictors	ulc.rq2
Unit-Weibull regression models for proportions	unitweib.reg
Zero adjusted Dirichlet regression	zadr zadr2

Package: Compositional 7.1

Compositional: Compositional Data Analysis

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