Running ‘checkinputs.R’ [15s/14s]
  Running ‘checkmethods.R’ [11s/20s]
  Running ‘checkmodule.R’ [8s/8s]
  Running ‘checkstudy.R’ [2s/3s]
Running the tests in ‘tests/checkstudy.R’ failed.
Complete output:
  > # Requires rjags:
  > if(require('rjags')){
  + 
  + 
  + 	library('runjags')
  + 	runjags.options(inits.warning=FALSE, rng.warning=FALSE, blockignore.warning=FALSE)
  + 
  + 	library('parallel')
  + 
  + 	testnum <- 1
  + 
  + 	themodel <- "
  + 	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# N, X
  + 	}"
  + 
  + 	# Simulate the data
  + 	set.seed(1)
  + 	N <- 20
  + 	X <- 1:N
  + 	Y <- rnorm(length(X), 2*X + 1, 1)
  + 
  + 	# Some initial values to use for 2 chains:
  + 
  + 	initfun <- function(chain){
  + 
  + 		# data is made available within this function when it
  + 		# is evaluated for each simulation:
  + 		stopifnot(length(data$X) == data$N)
  + 
  + 		m <- c(-10,10)[chain]
  + 		c <- c(10,-10)[chain]
  + 		precision <- c(0.01,100)[chain]
  + 
  + 		.RNG.seed <- chain
  + 		.RNG.name <- c("base::Super-Duper",
  + 		"base::Wichmann-Hill")[chain]
  + 
  + 		return(list(m=m, c=c, precision=precision,
  + 		.RNG.seed=.RNG.seed, .RNG.name=.RNG.name))
  + 	}
  + 
  + 	# A simple function that removes (over-writes with NA) one datapoint at a time:
  + 	datafun <- function(s){
  + 		simdata <- Y
  + 		simdata[s] <- NA
  + 		return(list(Y=simdata))
  + 	}
  + 
  + 
  + 	# Set up a cluster to use with the parLapply method:
  + 	cat('Running study test number', testnum, '\n'); testnum <- testnum+1
  + 	cl <- makeCluster(2)
  + 	# Call the simulations over the snow cluster:
  + 	results <- run.jags.study(simulations=4, model=themodel, datafunction=datafun,
  + 	targets=list(Y=Y, m=2, c=1), n.chains=2, inits=initfun, cl=cl)
  + 
  + 
  + 	m <- 'model{
  + 	d[1] ~ dpois(mu)
  + 	d[2] ~ dpois(mu)
  + 	d[3] ~ dpois(mu)
  + 	mu ~ dgamma(1,1)
  + 	#monitor# mu
  + 	#data# d
  + 	}'
  + 
  + 	##### Can't test any more than 2 spawned processes on winbuilder #####
  + 
  + 	cat('Running study test number', testnum, '\n'); testnum <- testnum+1
  + 	mu <- list(1,1)
  + 	d <- c(5, 4, 7)
  + 	jr <- run.jags(m, method='rjags', n.chains=2, inits=list(list(mu=1), list(mu=1)), silent.jags=TRUE)
  + 	# Drop 1 (would create 3 clusters except we pass it cl):
  + 	r <- drop.k(jr, dropvars='d', cl=cl)
  + 	stopCluster(cl)
  + 
  + 	# Drop k (use lapply so we don't create a cluster with 4 nodes):
  + 	cat('Running study test number', testnum, '\n'); testnum <- testnum+1
  + 	r <- drop.k(jr, dropvars='d', simulations=4, k=2, silent.jags=TRUE, parallel.method=lapply)
  + 	
  + 	cat("All study/drop-k checks passed\n")
  + 	
  + }else{
  + 	cat("Note: the rjags package is not installed, so the study/drop-k tests were skipped\n")
  + }
  Loading required package: rjags
  Loading required package: coda
  Linked to JAGS 4.3.0
  Loaded modules: basemod,bugs
  Running study test number 1 
  
  Starting a JAGS study at 22:49
  Testing the model and data for simulation 4...
  Error : The following error was encountered while attempting to run the JAGS model:  
     Error in parse.varnames(variable.names) : Invalid variable subset Y[1]
  
  Error in run.jags.study(simulations = 4, model = themodel, datafunction = datafun,  : 
    The test model returned an error - the simulation study was aborted
  Execution halted