temp-bikes/01 Agents/03-debug-BART.R

In ooelrich/oscbvar: Stuff for Bayesian vector autoregressions

library(parallel)
library(data.table)
library(ggplot2)

################################################################
### Debugging and exploring the stochastic volatility model  ###
################################################################

# Does separate runs produce differing predictions?
aa <- Sys.time()
barttest <- mclapply(
    rep(1, 4),
    bikes_bart,
    agc = list(1, 600, FALSE),
    nrep = 50000,
    nburn = 5000,
    mc.cores = 4
)
Sys.time() - aa 

all_bart  <- rbindlist(barttest, idcol = "run")
head(all_bart)
saveRDS(all_bart, "temp-bikes/01 Agents/all_bart.Rds")
# In case something goes horribly wrong
all_bart$run <- as.factor(all_bart$run)
all_bart[all_bart$t == 667, "lpdens"] <- 0
ggplot(all_bart, aes(x = t, y = lpdens, col = run)) + 
    geom_line() + 
    labs(title = "Lpdens of multiple runs of BART")
ggsave("temp-bikes/01 Agents/compare_bart.pdf")