runjags (version 2.0.2-8)

write.jagsfile: Write a complete JAGS model to a text file

Description

Writes the JAGS model, data, initial values and monitored variables etc to a file. The model can then be run using a call to link{run.jags} with the filename as the model argument.

Usage

write.jagsfile(runjags.object, file, remove.tags = TRUE, write.data = TRUE,
  write.inits = TRUE)

Arguments

runjags.object

a valid (but not necessarily updated) runjags object to be saved to file. No default.

file

a filename to which the model will be written. Note that any files already existing in that location will be overwritten with no warning (see new_unique for a way to generate unique filenames). No defa

remove.tags

should the runjags tags #data#, #inits#, #monitors#, #modules#, #factories#, #residual#, #fitted# and #response# be removed from the original model code before writing it to file? If left in, these may create conflicts with the tags automatically added t

write.data

should the data also be written to file? If FALSE, the model may not run from the file without specifying a new source of data.

write.inits

should the data also be written to file? If FALSE, the model may not run from the file without specifying new initial values.

Value

• Returns the filename that the model was saved to (invisibly)

References

Lunn D, Jackson C, Best N, Thomas A, Spiegelhalter D (2012). The BUGS book: A practical introduction to Bayesian analysis. CRC press.

See Also

read.jagsfile and run.jags for the reverse operation

Examples

# Set up a model:
# y = m x + c, assuming normal observation errors for y:

# Simulate the data
X <- 1:100
Y <- rnorm(length(X), 2*X + 10, 1)

# Model in the JAGS format
model <- "model {
for(i in 1 : N){
	Y[i] ~ dnorm(true.y[i], precision);
	true.y[i] <- (m * X[i]) + c
}
m ~ dunif(-1000,1000)
c ~ dunif(-1000,1000)
precision ~ dexp(1)
}"

# Data and initial values in a named list format,
# with explicit control over the random number
# generator used for each chain (optional):
data <- list(X=X, Y=Y, N=length(X))
inits1 <- list(m=1, c=1, precision=1,
.RNG.name="base::Super-Duper", .RNG.seed=1)
inits2 <- list(m=0.1, c=10, precision=1,
.RNG.name="base::Wichmann-Hill", .RNG.seed=2)

# Compile the model but don't update it (sample=0):
compiled <- run.jags(model=model, monitor=c("m", "c", "precision"),
data=data, n.chains=2, inits=list(inits1,inits2), sample=0)

# Save the complete model to a file:
filepath <- write.jagsfile(compiled, file='model.txt')

# And run the model from the file:
results <- run.jags(filepath)