wle.binomial {wle}R Documentation

Robust Estimation in the Binomial Model

Description

wle.binomial is used to robust estimate the proportion parameters via Weighted Likelihood.

Usage

wle.binomial(x, size, boot=30, group, num.sol=1, raf="HD", 
             tol=10^(-6), equal=10^(-3), max.iter=500)

Arguments

x a vector contain the number of success in each size trials.
size number of trials.
boot 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="SCHI2": Symmetric Chi-Squared Disparity RAF.
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.

Value

wle.binomial returns an object of class "wle.binomial".
Only print method is implemented for this class.
The object returned by wle.binomial are:

p the estimator of the proportion 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.
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

Examples

library(wle)

set.seed(1234)

x_rbinom(20,p=0.2,size=10)
wle.binomial(x,size=10)

x_c(rbinom(20,p=0.2,size=10),rbinom(10,p=0.9,size=10))
wle.binomial(x,size=10)