howardprior: Logarithm of Howard's dependent prior for two proportions
In bayesball/LearnBayes: Learning Bayesian Inference
Description
Usage
Arguments
Value
Author(s)
Examples
Description
Computes the logarithm of a dependent prior on two proportions
proposed by Howard in a Statistical Science paper in 1998.
Usage
1
howardprior(xy,par)
Arguments
xy
vector of proportions p1 and p2
par
vector containing parameter values alpha, beta, gamma, delta, sigma
Value
value of the log posterior
Author(s)
Jim Albert
Examples
1
2
3
param=c(1,1,1,1,2)
p=c(.1,.5)
howardprior(p,param)
bayesball/LearnBayes documentation built on May 11, 2019, 9:21 p.m.
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Description Usage Arguments Value Author(s) Examples
Description
Computes the logarithm of a dependent prior on two proportions proposed by Howard in a Statistical Science paper in 1998.
Usage
1 | howardprior(xy,par)
|
Arguments
xy |
vector of proportions p1 and p2 |
par |
vector containing parameter values alpha, beta, gamma, delta, sigma |
Value
value of the log posterior
Author(s)
Jim Albert
Examples
1 2 3 | param=c(1,1,1,1,2)
p=c(.1,.5)
howardprior(p,param)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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