Nothing
## ---- 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()
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