poissonMT (version 0.3-5)

poissonMTinitialParallel: Initial Robust Estimates based on MT robust method for fitting of Poisson Generalized Linear Models

Description

poissonMTinitialParallel is used to provides a robust initial estimate for fit generalized linear models. This is the parallel computing version. The model is specified by the x and y components.

Usage

poissonMTinitialParallel(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, parallel = c("no", "multicore", "snow"),
  ncpus = 1, cl = NULL)

Arguments

x

design matrix of dimension \(n \times p\).

y

vector of observations of length n.

stage2

logical, the second stage should be performed?

alpha

quantile orders used in the second stage.

tol

convergence tolerance for the parameter vector.

cc

tuning constant c for Tukey's bisquare psi-function.

psi

the name of the psi function. At the moment only the bisquare is available.

maxit

integer specifying the maximum number of IRWLS iterations.

zero

eigenvalues smaller than zero will be considered exactly equal to 0.

replace.small

all the observations y smaller than replace.small are replaced by replace.small value.

start

eventual starting values, as a reference, for the parameters in the linear predictor.

na.to.zero

logical, should the eventual NA in the coefficients be replaced by 0?

parallel

The type of parallel operation to be used. By default (none) no parallel is used.

ncpus

integer: number of processes to be used in parallel operation. Typically one would chose this to the number of available CPUs.

cl

An optional parallel or snow cluster for use if parallel = "snow". If not supplied, a cluster on the local machine is created for the duration of the poissonMTinitialParallel call.

Value

A list with the following components

coefficients1

initial value proposed at the end of the first stage.

obj1

value of the MT objective function at coefficients1.

coefficients2a

initial value proposed at the end of the first part od the second stage.

obj2a

value of the MT objective function at coefficients2a.

coefficients2b

initial value proposed at the end of the second part od the second stage.

obj2b

value of the MT objective function at coefficients2b.

coefficients

initial value proposed.

obj

value of the MT objective function at coefficients.

Details

This function is the same as function poissonMTinitial, however it can takes advantage of parallel computing.

References

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.

See Also

poissonMTinitial, poissonMT and poissonL2T

Examples

# NOT RUN {
  data(epilepsy)
  x <- model.matrix( ~ Age10 + Base4*Trt, data=epilepsy)
  poissonMTsetwd(tempdir())
  start <- poissonMTinitialParallel(x=x, y=epilepsy$Ysum)$coefficients
  start
# }