Description Usage Arguments Value See Also Examples
A wrapper function to make running mcmc fns on drake easier
1 2 | drake_mcmc(d, iter = 4000, warmup = iter/2, chains = 3, thin = 1,
whichmodel = NULL)
|
iter |
number of interations to be run (default=2000) |
chains |
number of chains to be run (default=3) |
thin |
when you want to thin (default=10) |
whichmodel |
characeter of which model you want to run |
dat |
response variable which follows binomial dist |
clusters |
number of clusters to be used (default=nchains) |
burnin |
number of samples to be used as burnin (technically adaption, see link below) |
inits |
expects TRUE/FALSE, if TRUE will use maximum likelihood to get starting values. Needs 3 chains. |
A MCMC object
http://www.mikemeredith.net/blog/2016/Adapt_or_burn.htm
1 | drake_mcmc(d, iter = 1000, chains = 3, clusters=3, warmup = iter/2, thin=1, whichmodel=="asg_common")
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