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Compositional (version 5.5)

Beta regression: 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.

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.

Details

Beta regression is fitted.

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

Run this code
# NOT RUN {
y <- rbeta(300, 3, 5)
x <- matrix( rnorm(300 * 2), ncol = 2)
beta.reg(y, x)
# }

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