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weightedScores (version 0.9.1)

Weighted Scores Method for Regression Models with Dependent Data

Description

Has functions that handle the steps for the weighted scores method in Nikoloulopoulos, Joe and Chaganty (2011, Biostatistics, 12: 653-665) for binary (logistic and probit), Poisson and negative binomial regression, with dependent data. Two versions of negative binomial regression from Cameron and Trivedi (1998) are used. Let NB(tau,xi) be a parametrization with probability mass function f(y; tau, xi) = Gamma(tau + y) xi^y / [ Gamma(tau) y! (1 + xi)^( tau + y )], for y = 0, 1, 2, ... , tau > 0 , xi > 0, with mean mu = tau*xi = exp(beta^T x) and variance tau*xi*(1 + xi), where x is a vector of covariates. For NB1, the parameter gamma is defined so that tau=mu/gamma, xi=gamma; for NB2, the parameter gamma is defined so that tau=1/gamma, xi=mu*gamma. In NB1, the convolution parameter tau is a function of the covariate x and xi is constant; in NB2, the convolution parameter tau is constant and xi is a function of the covariate x.

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Install

install.packages('weightedScores')

Monthly Downloads

100

Version

0.9.1

License

GPL (>= 2)

Last Published

November 6th, 2014

Functions in weightedScores (0.9.1)