"non-conforming parameters in function :" in simple linear regression using JAGS

Question

I am super new to JAGS and Bayesian statistics, and have simply been trying to follow the Chapter 22 on Bayesian statistics in Crawley's 2nd Edition R Book. I copy the code down exactly as it appears in the book for the simple linear model: growth = a + b *tannin, where there are 9 rows of two continuous variables: growth and tannins. The data and packages are this:

install.packages("R2jags")
library(R2jags)

growth <- c(12,10,8,11,6,7,2,3,3)
tannin <- c(0,1,2,3,4,5,6,7,8)
N <- c(1,2,3,4,5,6,7,8,9)
bay.df <- data.frame(growth,tannin,N)

The ASCII file looks like this:

model{
  for(i in 1:N) {
    growth[i] ~ dnorm(mu[i],tau)
    mu[i] <- a+b*tannin[i]
  }
  a ~ dnorm(0.0, 1.0E-4)
  b ~ dnorm(0.0, 1.0E-4)
  sigma <- 1.0/sqrt(tau)
  tau ~ dgamma(1.0E-3, 1.0E-3)
}

But then, when I use this code:

> practicemodel <- jags(data=data.jags,parameters.to.save = c("a","b","tau"),
+                   n.iter=100000, model.file="regression.bugs.txt", n.chains=3)

I get an error message that says:

module glm loaded
Compiling model graph
 Resolving undeclared variables
Deleting model

Error in jags.model(model.file, data = data, inits = init.values, n.chains = n.chains,  : 
  RUNTIME ERROR:
Non-conforming parameters in function :

I can't see anything wrong in the jags model code. Perhaps it is how you have included the data? Can you edit your question please to add data and any packages used. — user20650
– user20650, Commented Nov 8, 2019 at 2:06
okay, from the error message it looks like the : is the problem. It is fine in the model code, so perhaps you have passed the value for N incorrectly in the data.jags list of data. (From your description I'd of thought it should just be list(N=9, ...) — user20650
– user20650, Commented Nov 8, 2019 at 2:16
Thanks for all the tips - I tried importing the data from a csv and using read.csv and attach() R to bring up the data, but neither worked. I have edited the post to include the data, hopefully that clarifies something? Could you elaborate on the ":" theory? What would you put after ``` list(N=9, ... ``` ? — sebzee
– sebzee, Commented Nov 12, 2019 at 23:51
you are passing N incorrectly. When N is used in the for loop like this , it is to iterate through the observations and so should be the length of your data i.e. it is a single number not a vector. To be explicit data.jags = list(growth=bay.df$growth, tannin=bay.df$tannin, N=nrow(bay.df)) — user20650
– user20650, Commented Nov 13, 2019 at 9:04

user20650 · Accepted Answer · 2019-11-28 14:57:16Z

1

The problem has been solved!

Basically the change is from N <- (1,2...) to N <- 9, but there is one other solution as well, where no N is specified in the beginning. You can specify N inside the data.jags function as the number of rows in the data frame; data.jags = list(growth=bay.df$growth, tannin=bay.df$tannin, N=nrow(bay.df)).

Here is the new code:

# Make the data frame
growth <- c(12,10,8,11,6,7,2,3,3)
tannin <- c(0,1,2,3,4,5,6,7,8)
# CHANGED : This is for the JAGS code to know there are 9 rows of data
N <- 9 code
bay.df <- data.frame(growth,tannin)

library(R2jags)

# Now, write the Bugs model and save it in a text file
sink("regression.bugs.txt") #tell R to put the following into this file
cat("
model{
  for(i in 1:N) {
    growth[i] ~ dnorm(mu[i],tau)
    mu[i] <- a+b*tannin[i]
  }
  a ~ dnorm(0.0, 1.0E-4)
  b ~ dnorm(0.0, 1.0E-4)
  sigma <- 1.0/sqrt(tau)
  tau ~ dgamma(1.0E-3, 1.0E-3)
}
", fill=TRUE)
sink() #tells R to stop putting things into this file.

#tell jags the names of the variables containing the data
data.jags <- list("growth","tannin","N")

# run the JAGS function to produce the function:
practicemodel <- jags(data=data.jags,parameters.to.save = c("a","b","tau"),
                  n.iter=100000, model.file="regression.bugs.txt", n.chains=3)

# inspect the model output. Important to note that the output will
# be different every time because there's a stochastic element to the model
practicemodel 

# plots the information nicely, can visualize the error 
# margin for each parameter and deviance
plot(practicemodel)

Thanks for the help! I hope this helps others.

edited Nov 28, 2019 at 14:57

user20650

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answered Nov 22, 2019 at 18:39

sebzee

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1 Comment

user20650 Over a year ago

sebzee; regarding your comment on the different output - you can set the seed for each chain so that results are reproducible.

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