Compositional (version 2.0)

Dirichlet regression: Dirichlet regression

Description

Dirichlet regression.

Usage

diri.reg(y, x, plot = TRUE, xnew = NULL)
diri.reg2(y, x, xnew = NULL)

Arguments

y

A matrix with the compositional data (dependent variable). Zero values are not allowed.

x

The predictor variable(s), they can be either continnuous or categorical or both.

plot

A boolean variable specifying whether to plot the leverage values of the observations or not. This is taken into account only when xnew = NULL.

xnew

If you have new data use it, otherwise leave it NULL.

Value

A list including: A list including:

Details

A Dirichlet distribution is assumed for the regression. This involves numerical optimisation. The function "diri.reg2" allows for the covariates to be linked with the precisio parameter $\phi$ via the exponential link function $\phi = e^{x*b}$.

References

Maier, Marco J. (2014) DirichletReg: Dirichlet Regression for Compositional Data in R. Research Report Series/Department of Statistics and Mathematics, 125. WU Vienna University of Economics and Business, Vienna. http://epub.wu.ac.at/4077/1/Report125.pdf

Gueorguieva, Ralitza, Robert Rosenheck, and Daniel Zelterman (2008). Dirichlet component regression and its applications to psychiatric data. Computational statistics & data analysis 52(12): 5344-5355.

See Also

js.compreg, kl.compreg, ols.compreg, comp.reg, alfa.reg

Examples

x <- iris[, 4]
y <- iris[, 1:3]
mod1 <- diri.reg(y, x)
mod2 <-diri.reg2(y, x)
mod3 <- comp.reg(y, x)