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.