Growth model with t-distribution: continue mcmc
Load packages, read data and source custom scripts
rm(list = ls())
library(bamlss)#> Loading required package: coda#> Loading required package: colorspace#> Loading required package: mgcv#> Loading required package: nlme#> This is mgcv 1.8-31. For overview type 'help("mgcv-package")'.#>
#> Attaching package: 'bamlss'#> The following object is masked from 'package:mgcv':
#>
#> smooth.constructlibrary(gamlss.dist)#> Loading required package: MASSpath_proj <- day2day::git_path()
path_data <- file.path(path_proj, "data")
path_processed <- file.path(path_data, "processed")
path_modelled <- file.path(path_data, "modelled")
source(file.path(path_proj, "src", "43-mcmc-continue-light.R"))
source(file.path(path_proj, "src", "45-mcmc-reshape.R"))
source(file.path(path_proj, "src", "46-mcmc-get-last-sample.R"))
bwdata_model <- fst::read_fst(file.path(path_processed, "bwdata_41_model.fst"))
path_modelled_data <- file.path(path_modelled, "bw-20-growth-re-t.rds")
path_modelled_form <- gsub("(\\.rds)$", "-form\\1", path_modelled_data)
path_modelled_continue <- gsub("(\\.rds)$", "-continue\\1", path_modelled_data)
path_modelled_continue2 <- gsub("(\\.rds)$", "-continue2\\1", path_modelled_data)
path_modelled_sink <- gsub("\\.rds$", "\\.txt", path_modelled_continue2)
bamlss_model_continue <- readRDS(path_modelled_continue)
form <- readRDS(path_modelled_form)Continue with sampling
starting_value <- get_last_sample(bamlss_model_continue)
{
sink(path_modelled_sink)
bamlss_model <- bamlss(
form, family = TF, data = bwdata_model,
start = starting_value, optimizer = FALSE,
n.iter = 5000, burnin = 0, cores = 3, combine = FALSE, light = TRUE
)
sink()
}
readLines(path_modelled_sink)#> [1] "Starting the sampler..."
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#> [69] "|********************| 100% 0.00sec 705.93min"system.time(saveRDS(bamlss_model, file = path_modelled_continue2))#> user system elapsed
#> 11.436 0.080 11.789Time to execute the task
Only useful when executed with Rscript.
proc.time()#> user system elapsed
#> 127232.108 31.233 42490.239