update_par_nichisq: Update Parameters of a Normal-Inverse-Chi-Squared...

In RARtrials: Response-Adaptive Randomization in Clinical Trials

Update Parameters of a Normal-Inverse-Chi-Squared Distribution with Available Data

Description

Update parameters of a Normal-Inverse-Chi-Squared distribution

Usage

update_par_nichisq(y, par)

Arguments

y	observed data.
par	a vector of current parameters including mu, kappa, nu, sigsq from a Normal-Inverse-Chi-Squared distribution.

Details

This function updates parameters of a Normal-Inverse-Chi-Squared ((\mu,\sigma^2) \sim NIX( {\sf mean}=\mu, {\sf effective sample size}=\kappa, {\sf degrees of freedom}=\nu, {\sf variance}=\sigma^2/\kappa)) distribution with available data to parameters of a posterior Normal-Inverse-Gamma ((\mu,\sigma^2) \sim NIG({\sf mean}=m,{\sf variance}=V \times \sigma^2,{\sf shape}=a,{\sf rate}=b))distribution. Those updated parameters can be converted to parameters in a Normal-Inverse-Gamma distribution for continuous outcomes with unknown variances using convert_chisq_to_gamma.

Value

A list of parameters including mu, kappa, nu, sigsq for a posterior Normal-Inverse-Chi-Squared distribution incorporating available data.

References

\insertRef

Kevin2007RARtrials

Examples

para<-list(V=1/2,a=0.5,m=9.1/100,b=0.00002)
par<-convert_gamma_to_chisq(para)
set.seed(123451)
y1<-rnorm(100,0.091,0.009)
update_par_nichisq(y1, par)
set.seed(123452)
y2<-rnorm(90,0.09,0.009)
update_par_nichisq(y2, par)

RARtrials documentation built on April 4, 2025, 1:21 a.m.