SMIR (version 0.02)

treg: t-regression model fit

Description

Robust regression by modelling errors as $t$-distributed with known degrees of freedom rather than normal

Usage

treg(lm.object, r, verbose=TRUE)

Arguments

lm.object

An object of class "lm"

r

a vector of degrees of freedom

verbose

TRUE prints estimates for $-2 X $ log likelihood, sigma, and r at each interation.

Value

weights

working weights

disparity

disparity, i.e. full likelihood

tcoef

robust regression parameter estimates

r

degrees of freedom

Details

Fits the $t$ distribution for known degrees of freedom , $r$, and computes the profile likelihood and obtains the joint MLEs of the regression coefficients, sigma and disparity of a robust regression.

References

Aitkin, M., Francis, B., Hinde, J. and Darnell, R. (2008). Statistical modelling in R, OUP.

See Also

SMIR::summary.treg

Examples

library(SMIR)
data(stackloss)
stackloss.lm <- lm(y ~ x1 + x2 + x3, data = stackloss)
(stackloss.treg1.1 <- treg(stackloss.lm , r=1.1, verbose = FALSE) )