R: Log posterior of normal parameters when data is in grouped...

groupeddatapost {LearnBayes} | R Documentation

## Log posterior of normal parameters when data is in grouped form

### Description

Computes the log posterior density of (M,log S) for normal sampling where the data is observed in grouped form

### Usage

    groupeddatapost(theta,data)

### Arguments

`theta` | vector of parameter values M and log S
`data` | list with components int.lo, a vector of left endpoints, int.hi, a vector of right endpoints, and f, a vector of bin frequencies

### Value

value of the log posterior

### Author(s)

Jim Albert

### Examples

    int.lo=c(-Inf,10,15,20,25)
    int.hi=c(10,15,20,25,Inf)
    f=c(2,5,8,4,2)
    data=list(int.lo=int.lo,int.hi=int.hi,f=f)
    theta=c(20,1)
    groupeddatapost(theta,data)

[Package LearnBayes version 2.15 Index]