Reproducibility
Now that you've completed (and passed!) some Markov chain diagnostics, you're ready to finalize your RJAGS simulation. To this end, reproducibility is crucial. To obtain reproducible simulation output, you must set the seed of the RJAGS random number generator. This works differently than in base R. Instead of using set.seed(), you will specify a starting seed using inits = list(.RNG.name = "base::Wichmann-Hill", .RNG.seed = ___) when you compile your model.
Questo esercizio fa parte del corso
Bayesian Modeling with RJAGS
Istruzioni dell'esercizio
Run the provided code a few times. Notice that the
summary()statistics change each time.For reproducible results, supply the random number generator
initstojags.model(). Specify a starting seed of 1989.Run the new code a few times. Notice that the
summary()statistics do NOT change!
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# COMPILE the model
sleep_jags <- jags.model(textConnection(sleep_model), data = list(Y = sleep_study$diff_3))
# SIMULATE the posterior
sleep_sim <- coda.samples(model = sleep_jags, variable.names = c("m", "s"), n.iter = 10000)
# Summarize the m and s chains of sleep_sim
summary(sleep_sim)