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bradley.terry.post

Log posterior of a Bradley Terry random effects model

Computes the log posterior density of the talent parameters and the log standard deviation for a Bradley Terry model with normal random effects

bradley.terry.post(theta,data)

`theta`	vector of talent parameters and log standard deviation
`data`	data matrix with columns team1, team2, wins by team1, and wins by team2

value of the log posterior

Jim Albert

data(baseball.1964)
team.strengths=rep(0,10)
log.sigma=0
bradley.terry.post(c(team.strengths,log.sigma),baseball.1964)

Functions for Learning Bayesian Inference

v2.15.1

GPL (>= 2)

Authors

Jim Albert

Initial release

2018-03-18