poissonL2T {poissonMT} | R Documentation |
Fitting of Poisson Generalized Linear Models using MT method with L2 rho function
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
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 |
y |
vector of observations of length |
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 |
mprime.approx |
a function that return the value, for each linear predictor,
corresponding to the first derivative of |
na.to.zero |
logical, should the eventual |
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.
See Also
Examples
data(epilepsy)
x <- model.matrix( ~ Age10 + Base4*Trt, data=epilepsy)
poissonMTsetwd(tempdir())
Efit4 <- poissonL2T(x=x, y=epilepsy$Ysum)