Semiparametric proportional odds rate model

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Description

A rank-based empirical likelihood approach to two-sample proportional odds model and its goodness-of-fit. Let x1,...,xm and y1,...,yn be two independent samples from distributions F and G that satisfy

[G(x)/(1-G(x))]/[F(x)(1-F(x))]=G(x)(1-F(x))/[F(x)(1-G(x))]=θ

Function mele.theta.p returns rank-based maximum likelihood estimates of θ, θ-hat, and probability masses p1,...,pN of F at the sorted pooled sample values z1<...<zN, N=m+n.

Details

Package: sporm
Type: Package
Version: 1.0
Date: 2011-01-01
License: GPL 2.0 or newer
LazyLoad: yes

The most important function is mrle.sporm which returns the maximum rank-based likelihood estimates the proportionality paramter θ and the baseline distribution. Function ks.sporm is used to do the GOF test of the model assumption using a Kolmogorov-Smirnov type test statistic; confid.int.theta returns a confidence interval for θ; test.theta does the hypothesis testing for θ; Ell.Theta calculates the profile loglikelihood l(θ) on interval (θ1,θ2) which contains θ-hat; and plotor plot the empirical odds ratio. Functions newton.theta, dd.est and phi can be used to calculate other initials. There are few internal functions: V.theta, H.Binv, grad.hessinv, ks.stat, and elltheta. Dataset RadarTube contains the failure times (in days) of two types of radar tubes.

Author(s)

Zhong Guan <zguan@iusb.edu>; Cheng Peng <cpeng@usm.maine.edu>

Zhong Guan <zguan@iusb.edu>

References

Zhong Guan and Cheng Peng (2011), "A rank-based empirical likelihood approach to two-sample proportional odds model and its goodness-of-fit", Journal of Nonparametric Statistics, to appear.