treg {SMIR} | R Documentation |
Robust regression by modelling errors as $t$-distributed with known degrees of freedom rather than normal
treg(lm.object, r, verbose=TRUE)
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. |
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.
an object of class ``treg''
weights | working weights |
disparity | disparity, i.e. full likelihood |
tcoef | robust regression parameter estimates |
r | degrees of freedom |
sigma | estimate of residual standard deviation |
Aitkin, M., Francis, B., Hinde, J. and Darnell, R. (2008). Statistical modelling in R, OUP.
SMIR::summary.treg
library(SMIR) data(stackloss) stackloss.lm <- lm(y ~ x1 + x2 + x3, data = stackloss) (stackloss.treg1.1 <- treg(stackloss.lm , r=1.1, verbose = FALSE) )