Beta regression
Beta regression.
beta.reg(y, x, xnew = NULL)
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. |
Beta regression is fitted.
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. |
Michail Tsagris
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr
Ferrari S.L.P. and Cribari-Neto F. (2004). Beta Regression for Modelling Rates and Proportions. Journal of Applied Statistics, 31(7): 799-815.
y <- rbeta(300, 3, 5) x <- matrix( rnorm(300 * 2), ncol = 2) beta.reg(y, x)
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