bayesforecast (version 1.0.1)

loglik: Extract posterior sample of the accumulated log-likelihood from a varstan object

Description

Convenience function for extracting the posterior sample of the accumulated log-likelihood array from a fitted varstan object.

Usage

loglik(object, permuted = TRUE)

Arguments

object

A varstan object of the time series fitted model.

permuted

A logical scalar indicating whether the draws after the warmup period in each chain should be permuted and merged. If FALSE, the original order is kept. For each stanfit object, the permutation is fixed (i.e., extracting samples a second time will give the same sequence of iterations).

Value

A real value with the accumulated log likelihood.

References

Vehtari, A., Gelman, A., & Gabry J. (2016). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. In Statistics and Computing, doi:10.1007/s11222-016-9696-4.

Gelman, A., Hwang, J., & Vehtari, A. (2014). Understanding predictive information criteria for Bayesian models. Statistics and Computing. 24, 997-1016.

Watanabe, S. (2010). Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. The Journal of Machine Learning Research. 11, 3571-3594.

Examples

# NOT RUN {
 library(astsa)
 model = Sarima(birth,order = c(0,1,2),seasonal = c(1,1,1))
 fit1 = varstan(model,iter = 500,chains = 1)

 log1 = loglik(fit1)
 log1
# }
# NOT RUN {
# }