poissonMTinitial is used to provides a robust initial estimate
for fit generalized linear models.
The model is specified by the x and y components.
poissonMTinitial(x, y, stage2 = TRUE, alpha = c(0.025, 0.025),
tol = 1e-04, cc = 2.3, psi = "bisquare", maxit = 20,
zero = sqrt(.Machine$double.eps), replace.small = 0.5, start = NULL,
na.to.zero = TRUE)design matrix of dimension \(n \times p\).
vector of observations of length n.
logical, the second stage should be performed?
quantile orders used in the second stage.
convergence tolerance for the parameter vector.
tuning constant c for Tukey's bisquare psi-function.
the name of the psi function. At the moment only the
bisquare is available.
integer specifying the maximum number of IRWLS iterations.
eigenvalues smaller than zero will be considered exactly equal to 0.
all the observations y smaller than replace.small
are replaced by replace.small value.
eventual starting values, as a reference, for the parameters in the linear predictor.
logical, should the eventual NA in the coefficients
be replaced by 0?
A list with the following components
initial value proposed at the end of the first stage.
value of the MT objective function at coefficients1.
initial value proposed at the end of the first part od the second stage.
value of the MT objective function at coefficients2a.
initial value proposed at the end of the second part od the second stage.
value of the MT objective function at coefficients2b.
initial value proposed.
value of the MT objective function at coefficients.
C. Agostinelli, M. Valdora and V.J Yohai (2018) Initial Robust Estimation in Generalized Linear Models with a Large Number of Covariates. Submitted.
M. Valdora and V.J. Yohai (2014) Robust estimators for generalized linear models. Journal of Statistical Planning and Inference, 146, 31-48.
poissonMT and poissonL2T
# NOT RUN {
data(epilepsy)
x <- model.matrix( ~ Age10 + Base4*Trt, data=epilepsy)
poissonMTsetwd(tempdir())
start <- poissonMTinitial(x=x, y=epilepsy$Ysum)$coefficients
start
# }
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