the number of starting points based on boostrap subsamples to use in the search of the roots.
group
the dimension of the bootstap subsamples. The default value is max(round(length(x)/4),2).
num.sol
maximum number of roots to be searched.
raf
type of Residual adjustment function to be use:
raf="HD": Hellinger Distance RAF,
raf="NED": Negative Exponential Disparity RAF,
raf="GKL": Generalized Kullback-Leibler RAF family
with parameter tau.
raf="PWD": Power Divergence Measure RAF family
with parameter tau.
raf="SCHI2": Symmetric Chi-Squared Disparity RAF.
tau
this is to set the member inside the GKL and PWD family. It
must be in [0,1] for GKL and in [-1, Inf] for PWD.
tol
the absolute accuracy to be used to achieve convergence of the algorithm.
equal
the absolute value for which two roots are considered the same. (This parameter must be greater than tol).
max.iter
maximum number of iterations.
verbose
if TRUE warnings are printed.
Value
wle.poisson returns an object of class"wle.poisson".
Only print method is implemented for this class.
The object returned by wle.poisson are:
lambda
the estimator of the lambda parameter, one value for each root found.
tot.weights
the sum of the weights divide by the number of observations, one value for each root found.
weights
the weights associated to each observation, one column vector for each root found.
f.density
the non-parametric density estimation.
m.density
the smoothed model.
delta
the Pearson residuals.
call
the match.call().
tot.sol
the number of solutions found.
not.conv
the number of starting points that does not converge after the max.iter iteration are reached.
Author(s)
Claudio Agostinelli
References
Markatou, M., Basu, A., and Lindsay, B.G., (1997) Weighted likelihood estimating equations: The discrete case with applications to logistic regression, Journal of Statistical Planning and Inference, 57, 215-232.
Agostinelli, C., (1998) Inferenza statistica robusta basata sulla funzione di verosimiglianza pesata: alcuni sviluppi, Ph.D Thesis, Department of Statistics, University of Padova.
Examples
library(wle)
set.seed(1234)
x <- rpois(40,5)
wle.poisson(x)
x <- c(rpois(40,5),rpois(10,20))
wle.poisson(x)
providing 
.