jagsresults: Print results for specified rjags or mcmc.list parameters
In johnbaums/jagstools: Easy access to rjags and mcmc.list parameters

Description Usage Arguments Value See Also Examples

View source: R/jagsresults.R

Prints results for rjags or mcmc.list parameters, which are specified with a regular expression, or by exact name.

1 2	jagsresults(x, params, regex = FALSE, invert = FALSE, probs = c(0.025, 0.25, 0.5, 0.75, 0.975), signif, ...)

`x`	The `rjags`, `rjags.parallel`, or `mcmc.list` object for which results will be printed.
`params`	Character vector or a regular expression pattern. The parameters for which results will be printed (unless `invert` is `FALSE`, in which case results for all parameters other than those given in `params` will be returned). If `regex` is `FALSE`, only those parameters that match `params` exactly will be returned. If `regex` is `TRUE`, `param` should be a character string giving the regular expression pattern to be matched.
`regex`	Logical. If `regex` is `TRUE`, then `param` is expected to be a single string giving a text pattern to be matched. Parameters with names matching the pattern will be returned (unless `invert` is `TRUE`, which results in all parameters that do not match the pattern being returned). Text pattern matching uses regular expressions (`regex`).
`invert`	Logical. If `invert` is `TRUE`, only those parameters that do not match elements of `params` will be returned.
`probs`	A numeric vector of probabilities within range [0, 1], representing the sample quantiles to be calculated and returned.
`signif`	If supplied, all columns other than `n.eff` will have their values rounded such that the most extreme value has the specified number of significant digits.
`...`	Additional arguments accepted by `grep`, e.g. `perl=TRUE`, to allow look-around pattern matching.

A matrix with one row for each parameter that matches param, and one column for each of mean, sd, percentiles 2.5, 25, 50, 75, and 97.5. In addition, if x is an rjags object, columns for Rhat and neff are returned.

rhats for simplified rhat output, rearray for recovering array structure of vector-valued parameters.

## Data
N <- 100
temp <- runif(N)
rain <- runif(N)
wind <- runif(N)
a <- 0.13
beta.temp <- 1.3
beta.rain <- 0.86
beta.wind <- -0.44
sd <- 0.16
y <- rnorm(N, a + beta.temp*temp + beta.rain*rain + beta.wind*wind, sd)
dat <- list(N=N, temp=temp, rain=rain, wind=wind, y=y)

### jags example
library(R2jags)

## Model
M <- function() {
  for (i in 1:N) {
    y[i] ~ dnorm(y.hat[i], sd^-2)
    y.hat[i] <- a + beta.temp*temp[i] + beta.rain*rain[i] + beta.wind*wind[i]
    resid[i] <- y[i] - y.hat[i]
  }
  sd ~ dunif(0, 100)
  a ~ dnorm(0, 0.0001)
  beta.temp ~ dnorm(0, 0.0001)
  beta.rain ~ dnorm(0, 0.0001)
  beta.wind ~ dnorm(0, 0.0001)
}

## Fit model
jagsfit <- jags(dat, inits=NULL, 
                parameters.to.save=c('a', 'beta.temp', 'beta.rain', 
                                     'beta.wind', 'sd', 'resid'), 
                model.file=M, n.iter=10000)

## Output
# model summary
jagsfit

# Results for beta.rain only
jagsresults(x=jagsfit, param='beta.rain')

# Results for 'a' and 'sd' only
jagsresults(x=jagsfit, param=c('a', 'sd'))
jagsresults(x=jagsfit, param=c('a', 'sd'), 
            probs=c(0.01, 0.025, 0.1, 0.25, 0.5, 0.75, 0.9, 0.975))

# Results for all parameters including the string 'beta'
jagsresults(x=jagsfit, param='beta', regex=TRUE)

# Results for all parameters not including the string 'beta'
jagsresults(x=jagsfit, param='beta', regex=TRUE, invert=TRUE)

# Note that the above is NOT equivalent to the following, which returns all
# parameters that are not EXACTLY equal to 'beta'.
jagsresults(x=jagsfit, param='beta', invert=TRUE)

# Results for all parameters beginning with 'b' or including 'sd'.
jagsresults(x=jagsfit, param='^b|sd', regex=TRUE)

# Results for all parameters not beginning with 'beta'.
# This is equivalent to using param='^beta' with invert=TRUE and regex=TRUE
jagsresults(x=jagsfit, param='^(?!beta)', regex=TRUE, perl=TRUE)

## mcmc.list example
library(rjags)
simgrowth$model$recompile()
simgrowth_mcmclist <- 
  coda.samples(simgrowth$model, 
               setdiff(simgrowth$parameters.to.save, 'deviance'), 1000)
is(simgrowth_mcmclist)
jagsresults(simgrowth_mcmclist, c('b[3]', 'log.r[2,1]'))
jagsresults(simgrowth_mcmclist, c('b[3]', 'log.r[2,1]'), invert=TRUE)
jagsresults(simgrowth_mcmclist, c('lambda[3,1]', 'sd.b'))
jagsresults(simgrowth_mcmclist, c('lambda\\[3,1\\]|sd\\.'), regex=TRUE)