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ELYP (version 0.7-1)

Empirical Likelihood Analysis for the Cox Model and Yang-Prentice (2005) Model

Description

Empirical likelihood ratio tests for the Yang and Prentice (short/long term hazard ratio) models. Empirical likelihood tests within a Cox model, for parameters defined via both baseline hazard function and regression parameters.

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Version

Install

install.packages('ELYP')

Monthly Downloads

528

Version

0.7-1

License

GPL (>= 2)

Maintainer

Mai Zhou

Last Published

March 27th, 2015

Functions in ELYP (0.7-1)

findU3

Find the Wilks Confidence Interval Upper Bound from the Given Empirical Likelihood Ratio Function
CoxFindU2

Find the Wilks Confidence Interval Upper Bound for Efun from the Empirical Likelihood Ratio Function CoxEL( ).
findU4

Find the Wilks Confidence Interval Upper Bound from the Given Empirical Likelihood Ratio Function
ELYP-internal

Internal ELYP functions
BJfindL2

Find the Wilks Confidence Interval Lower Bound for Betafun from the 2 dimensional Buckley-James Empirical Likelihood Ratio Function
fitYP4

Compute Alpha and Baseline Hazard for the Given Data, Given Parameters beta1, beta2. Also, compute the empirical likelihood value.
CoxFindU3

Find the Wilks Confidence Interval Upper Bound from the Given Empirical Likelihood Ratio Function
findL4

Find the Wilks Confidence Interval Lower Bound from the Given Empirical Likelihood Ratio Function
findU2d

Find the Wilks Confidence Interval Upper Bound from the Given 2-d Empirical Likelihood Ratio Function
BJfindU2

Find the Wilks Confidence Interval Upper Bound for Betafun from the 2 dimensional Buckley-James Empirical Likelihood Ratio Function
myLLfun2

Compute Baseline Hazard for the Given Data and Parameters beta1, beta2, alpha, lam. Also Compute the empirical likelihood value.
CoxEL

Compute Empirical Likelihood and Partial Likelihood of Cox model for Testing the beta and Baseline jointly.
CoxFindL3

Find the Wilks Confidence Interval Upper Bound from the Given Empirical Likelihood Ratio Function
CoxFindL2

Find the Wilks Confidence Interval Lower Bound for Efun from the Empirical Likelihood Ratio Function CoxEL
GastricCancer

Gastric Cancer Data
fitYP3

Compute Baseline Hazard for the Given Data, Given Parameters: beta1, beta2, lam, and fun. Also, Given the Baseline, Compute the empirical likelihood value.
ELrange

Find the Ractangular parameter region where EL is Only 4 below the Maximum Value.
Pfun

The Hazard Ratio in YP Model as a Function of beta1 beta2 and Mulam.
simuDataYP

Generate random times that follow the YP model with the Given Parameters th1, th2, and alphaX.
smallcell

Smallcell Lung Cancer Data
Pfun2

The Hazard Ratio in YP Model as a Function of beta1, beta2, a, X, and Mulam.
findL2d

Find the Wilks Confidence Interval Lower Bound from the Given 2-d Empirical Likelihood Ratio Function
myLLfun

Compute Baseline Hazard for the Given Data and Parameters beta1, beta2, lam. Also Compute the empirical likelihood value.
findL3

Find the Wilks Confidence Interval Lower Bound from the Given Empirical Likelihood Ratio Function
findU32

Find the Wilks Confidence Interval Upper Bound from the Given Empirical Likelihood Ratio Function
fitYP41

Compute the Baseline Hazard for the Given Data, given Parameters beta1, beta2. Also, compute the empirical likelihood value.