poissonSSinitial: Initial Robust Estimates based on SubSampling method for...
In poissonMT: Robust M-Estimators Based on Transformations for Poisson Model

Description Usage Arguments Value Author(s) References See Also Examples

poissonSSinitial is used to provides a robust initial estimate for fit generalized linear models. The model is specified by the x and y components.

1 2	poissonSSinitial(x, y, nsubm, size = ncol(x), cc = 2.3, psi = "bisquare", na.to.zero = TRUE, trace.lev = 0)

`x`	design matrix of dimension n p*.
`y`	vector of observations of length `n`.
`nsubm`	the number of subsamples to take for finding an initial estimate.
`size`	size of the subsamples.
`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.
`na.to.zero`	logical, should the eventual `NA` in the coefficients be replaced by `0`?
`trace.lev`	logical (or integer) indicating if intermediate results should be printed; defaults to `0` (the same as `FALSE`).

A list with the following components

`coefficients`	initial value proposed.
`obj`	value of the MT objective function at `coefficients`.
`nOksamples`	number of subsamples without errors.

Claudio Agostinelli, Marina Valdora and Victor J. Yohai

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.

poissonMTinitial

  data(epilepsy)
  x <- model.matrix( ~ Age10 + Base4*Trt, data=epilepsy)
  start <- poissonSSinitial(x=x, y=epilepsy$Ysum, nsubm=100)$coefficients
  start