if (requireNamespace("neojags", quietly = TRUE)){
neojags::load.neojagsmodule()
}
#> module neojags loaded
if (requireNamespace("neojags", quietly = TRUE)){
library(rjags)
}
#> Loading required package: coda
#> Linked to JAGS 4.3.1
#> Loaded modules: basemod,bugs,neojags
modelv <- jags.model(textConnection(mod), n.chains=1, inits = list(".RNG.name" = "base::Wichmann-Hill",".RNG.seed" = 314159))
#> Compiling model graph
#> Resolving undeclared variables
#> Allocating nodes
#> Graph information:
#> Observed stochastic nodes: 0
#> Unobserved stochastic nodes: 100
#> Total graph size: 103
#>
#> Initializing model
model <- jags.model(textConnection(model_string), data = list(x=c(x)),n.chains=2)
#> Compiling model graph
#> Resolving undeclared variables
#> Allocating nodes
#> Graph information:
#> Observed stochastic nodes: 100
#> Unobserved stochastic nodes: 4
#> Total graph size: 107
#>
#> Initializing model
summary(samples)
#>
#> Iterations = 1001:3000
#> Thinning interval = 1
#> Number of chains = 2
#> Sample size per chain = 2000
#>
#> 1. Empirical mean and standard deviation for each variable,
#> plus standard error of the mean:
#>
#> Mean SD Naive SE Time-series SE
#> mu 1.9984 0.009952 0.0001573 0.0001997
#> nu1 0.7436 0.064657 0.0010223 0.0024146
#> nu2 1.1670 0.155830 0.0024639 0.0053501
#> tau 0.9543 0.260051 0.0041118 0.0104381
#>
#> 2. Quantiles for each variable:
#>
#> 2.5% 25% 50% 75% 97.5%
#> mu 1.9788 1.9919 1.9985 2.0052 2.0182
#> nu1 0.6300 0.6981 0.7407 0.7832 0.8835
#> nu2 0.9025 1.0538 1.1539 1.2655 1.5128
#> tau 0.5415 0.7645 0.9209 1.1066 1.5428
model_string1 <- "
model {
d <- djskew.ep(0.5,2,2,2,2)
p <- pjskew.ep(0.5,2,2,2,2)
q <- qjskew.ep(0.5,2,2,2,2)
}
"
summary(samples1)
#>
#> Iterations = 1:2
#> Thinning interval = 1
#> Number of chains = 2
#> Sample size per chain = 2
#>
#> 1. Empirical mean and standard deviation for each variable,
#> plus standard error of the mean:
#>
#> Mean SD Naive SE Time-series SE
#> d 0.008864 0 0 0
#> p 0.001350 0 0 0
#> q 2.000000 0 0 0
#>
#> 2. Quantiles for each variable:
#>
#> 2.5% 25% 50% 75% 97.5%
#> d 0.008864 0.008864 0.008864 0.008864 0.008864
#> p 0.001350 0.001350 0.001350 0.001350 0.001350
#> q 2.000000 2.000000 2.000000 2.000000 2.000000