Beta regression {Compositional}R Documentation

Beta regression

Description

Beta regression.

Usage

beta.reg(y, x, xnew = NULL)

Arguments

y

The response variable. It must be a numerical vector with proportions excluding 0 and 1.

x

The indendent variable(s). It can be a vector, a matrix or a dataframe with continuous only variables, a data frame with mixed or only categorical variables.

xnew

If you have new values for the predictor variables (dataset) whose response values you want to predict insert them here.

Details

Beta regression is fitted.

Value

A list including:

phi

The estimated precision parameter.

info

A matrix with the estimated regression parameters, their standard errors, Wald statistics and associated p-values.

loglik

The log-likelihood of the regression model.

est

The estimated values if xnew is not NULL.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

References

Ferrari S.L.P. and Cribari-Neto F. (2004). Beta Regression for Modelling Rates and Proportions. Journal of Applied Statistics, 31(7): 799-815.

See Also

beta.est, prop.reg, diri.reg

Examples

y <- rbeta(300, 3, 5)
x <- matrix( rnorm(300 * 2), ncol = 2)
beta.reg(y, x)

[Package Compositional version 5.2 Index]