MXM (version 0.9.7)

Beta regression: Beta regression

Description

Beta regression.

Usage

beta.mod(target, dataset, wei = NULL, xnew= NULL) 
beta.reg(target, dataset, wei = NULL)

Arguments

target

The target (dependent) variable. It must be a numerical vector with integers.

dataset

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.

wei

A vector of weights to be used for weighted regression. The default value is NULL.

xnew

If you have new values for the predictor variables (dataset) whose target variable you want to predict insert them here. If you put the "dataset" or leave it NULL it will calculate the regression fitted values.

Value

A list including: A list including:

Details

The beta regression is fitted. The "beta.reg" is an internal wrapper function and is used for speed up purposes. It is not to be called directly by the user unless they know what they are doing.

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.regs, testIndBeta, reg.fit, ridge.reg

Examples

y <- rbeta(500, 3, 5)
x <- matrix( rnorm(500 * 2), ncol = 2)
a1 <- beta.mod(y, x)
w <- runif(500)
a2 <- beta.mod(y, x, w)