rbi.helpers.R
In rbi.helpers: 'rbi' Helper Functions

## ----include = FALSE----------------------------------------------------------
NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")), "true") # nolint
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = NOT_CRAN
)

## ----eval = FALSE-------------------------------------------------------------
# install.packages("rbi.helpers")

## ----eval = FALSE-------------------------------------------------------------
# remotes::install_github("sbfnk/rbi.helpers")

## ----eval = FALSE-------------------------------------------------------------
# library("rbi")
# library("rbi.helpers")

## ----echo = FALSE-------------------------------------------------------------
# suppressPackageStartupMessages(library("rbi"))
# suppressPackageStartupMessages(library("rbi.helpers"))

## ----eval = NOT_CRAN----------------------------------------------------------
# model_file <- system.file(package = "rbi", "SIR.bi") # file included in package
# sir_model <- bi_model(model_file) # load model
# set.seed(1001912)
# sir_data <- bi_generate_dataset(sir_model, end_time = 16 * 7, noutputs = 16)

## -----------------------------------------------------------------------------
# bi_prior <- sample(
#   proposal = "prior", sir_model, nsamples = 1000, end_time = 16 * 7,
#   nparticles = 4, obs = sir_data, seed = 1234
# )

## -----------------------------------------------------------------------------
# adapted <- adapt_particles(bi_prior)

## -----------------------------------------------------------------------------
# adapted$options$nparticles

## -----------------------------------------------------------------------------
# adapted <- adapt_proposal(adapted, min = 0.05, max = 0.4)

## -----------------------------------------------------------------------------
# bi_read(adapted, file = "input")

## -----------------------------------------------------------------------------
# posterior <- sample(adapted)
# DIC(posterior)

## -----------------------------------------------------------------------------
# res <- numeric_to_time(posterior, unit = "day", origin = as.Date("2018-04-01"))
# head(res$Z)

## -----------------------------------------------------------------------------
# orig <- time_to_numeric(res, unit = "day", origin = as.Date("2018-04-01"))
# head(orig$Z)

## -----------------------------------------------------------------------------
# posterior <- sample(
#   proposal = "prior", sir_model, nsamples = 1000,
#   end_time = 16 * 7, nparticles = 4, obs = sir_data, seed = 1234
# ) |>
#   adapt_particles() |>
#   adapt_proposal(min = 0.05, max = 0.4) |>
#   sample(nsamples = 5000) |>
#   sample_obs()