gsbBayesUpdate: Bayesian Update

In gsbDesign: Group Sequential Bayes Design

Bayesian Update

Description

Bayesian update from prior and data to posterior for normally distributed data with known sigma.

Usage

gsbBayesUpdate(alpha, beta, meanData, precisionData, with.alpha = TRUE)

Arguments

alpha	vector of prior means.
beta	vector of prior precisions.
meanData	vector of means from data.
precisionData	vector of precisions from data.
with.alpha	logical. If with.alpha = TRUE, alpha, beta, meanData and precisionData has to be specified and the posterior means, posterior precisions and weights are returned. Else only beta and precisionData has to be specified and the posterior precisions and weights are returned.

Value

alpha	posterior means. Only if with.alpha = TRUE.
beta	posterior precisions.
weight	weights of the priors relative to the whole information after updating.

Note

This function is used in the function gsb().

Author(s)

Florian Gerber <[e-mail]>, Thomas Gsponer

See Also

gsb

Examples

## One dimensional case, with.alpha = FALSE
gsbBayesUpdate(beta=10,precisionData=20, with.alpha=FALSE)

## Two dimensional case, with.alpha = TRUE
gsbBayesUpdate(alpha=c(5,6),beta=c(10,11),meanData=c(10,11),
               precisionData=c(20,21),with.alpha=TRUE)

gsbDesign documentation built on May 29, 2024, 4:19 a.m.