# poissonL2T: Fitting of Poisson Generalized Linear Models using MT method... In poissonMT: Robust M-Estimators Based on Transformations for Poisson Model

## Description

`poissonL2T` is used to fit generalized linear models by MT method with L2 rho function. The model is specified by the `x` and `y` components. Since the L2 rho function is used the method is not robust.

## Usage

 ```1 2``` ``` poissonL2T(x, y, start = NULL, tol = 1e-08, maxit = 100, m.approx = NULL, mprime.approx = NULL, na.to.zero = TRUE) ```

## Arguments

 `x` design matrix of dimension n * p. `y` vector of observations of length `n`. `start` starting values for the parameters in the linear predictor. `tol` convergence tolerance for the parameter vector. `maxit` integer specifying the maximum number of IRWLS iterations. `m.approx` a function that return the value, for each linear predictor, that makes the estimating equation Fisher consistent. If `NULL` the default internal function is used. `mprime.approx` a function that return the value, for each linear predictor, corresponding to the first derivative of `m.approx`. If `NULL` the default internal function is used. `na.to.zero` logical, should the eventual `NA` in the coefficients be replaced by `0`?

## Value

A vector with the estimated coefficients.

## Author(s)

Claudio Agostinelli, Marina Valdora and Victor J. Yohai

## 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.

`poissonMT`
 ```1 2 3 4``` ``` data(epilepsy) x <- model.matrix( ~ Age10 + Base4*Trt, data=epilepsy) poissonMTsetwd(tempdir()) Efit4 <- poissonL2T(x=x, y=epilepsy\$Ysum) ```