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 |