Description Usage Arguments Value See Also Examples
Runs Asymmetric Gaussian MCMC with a hierarchical mean structure accross the groups
1 2 | normal_hier(y, x, count, group, priors, niter = 2000, nchains = 3,
nclusters = nchains, burnin = niter/2, thin = 10)
|
y |
response variable which follows binomial dist |
x |
explanatory variable |
count |
n in binomial dist |
group |
groups of response |
priors |
list of priors |
niter |
number of interations to be run (default=2000) |
nchains |
number of chains to be run (default=3) |
nclusters |
number of clusters to be used (default=nchains) |
burnin |
number of samples to be used as burnin (technically adaption, see link below) |
thin |
when you want to thin (default=10) |
A MCMC object
http://www.mikemeredith.net/blog/2016/Adapt_or_burn.htm
1 2 3 4 5 | priors <- list()
priors$vm <- 10
priors$mx <- 15
priors$vmx <- 10
priors$vs <- 10
|
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