CoxFindU2 {ELYP} R Documentation

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

### Description

This function uses simple search to find the upper 95% Wilks confidence limits based on the log likelihood function supplied. This is a sister function to CoxFindL2().

### Usage

CoxFindU2(BetaMLE, StepSize, Hfun, Efun, y, d, Z, level=3.84)


### Arguments

 BetaMLE a scalar: the NPMLE beta1 hat. StepSize a vector of length 2. Approximate length of the 2 confidence intervals: beta1, and lambda. It is the initial search step size. Hfun a function that defines the baseline feature: mu=int f(t) dH(t). Efun a function that takes the input of 2 parameter values (beta1, and Mulam) and returns a parameter that we wish to find the confidence Interval Upper Value. The two input variables must be called beta and theta. y a vector of censored survival times. d a vector of 0 and 1, censoring indicator. Z covariates for the Cox model level Confidence Level. Use chi-square(df=1), but calibration possible.

### Details

Basically we repeatedly testing the value of the parameter, until we find those which the -2 log likelihood value is equal to 3.84 (or other level, if set differently).

### Value

A list with the following components:

 Upper the upper confidence bound. maxParameterNloglik Final values of the 4 parameters, and the log likelihood.

Mai Zhou

### References

Zhou, M. (2002). Computing censored empirical likelihood ratio by EM algorithm. JCGS

### Examples

## See example in CoxFindL2.
## Here Mulam is the value of int g(t) d H(t) = Mulam
## For example g(t) = I[ t <= 2.0 ]; look inside myLLfun().


[Package ELYP version 0.7-5 Index]