run.model: Create and run rcppbugs models.

In armstrtw/rcppbugs: R binding for cppbugs

Description

The create.model function creates a model object. The run.model function simulates an mcmc chain of the nodes in the model. After the completion of run.model, the history of the run is returned as a named list.

Usage

create.model(...)
run.model(m, iterations, burn, adapt, thin)
get.ar(x)

Arguments

m	the rcppbugs model object.
iterations	how many iterations to sample.
burn	how many iterations to use for burnin.
adapt	how many iterations to use for the adaptive period.
thin	how frequently to record traces of the model nodes.
...	rcppbugs objects to use as the nodes of the model.
x	the result of an rcppbugs run.

Value

create.model returns a mcmc.model model object. run.model returns a named list containing the historical traces of the model run. get.ar returns the acceptance ratio of an MCMC run

Author(s)

rcppbugs was written by Whit Armstrong.

References

https://github.com/armstrtw/CppBugs

See Also

logp

Examples

library(rcppbugs)


NR <- 1e2L
NC <- 2L
y <- matrix(rnorm(NR,1) + 10,nr=NR,nc=1L)
X <- matrix(nr=NR,nc=NC)
X[,1] <- 1
X[,2] <- y + rnorm(NR)/2 - 10

## RCppBugs Model
b <- mcmc.normal(rnorm(NC),mu=0,tau=0.0001)
tau.y <- mcmc.gamma(sd(as.vector(y)),alpha=0.1,beta=0.1)
y.hat <- linear(X,b)
y.lik <- mcmc.normal(y,mu=y.hat,tau=tau.y,observed=TRUE)
m <- create.model(b, tau.y, y.hat, y.lik)


runtime <- system.time(ans <- run.model(m, iterations=1e2L, burn=1e2L, adapt=1e3L, thin=10L))
print(get.ar(ans))

print(apply(ans[["b"]],2,mean))

armstrtw/rcppbugs documentation built on May 10, 2019, 1:42 p.m.