spim_control: High-level control
In mrc-ide/spimalot: Support for 'sircovid'

spim_control

R Documentation

High-level control

Description

High-level control.

Usage

spim_control(
  short_run,
  n_chains,
  deterministic = FALSE,
  multiregion = FALSE,
  rt = TRUE,
  severity = FALSE,
  intrinsic_severity = FALSE,
  simulate = FALSE,
  demography = FALSE,
  date_restart = NULL,
  n_particles = 192,
  n_mcmc = 1500,
  burnin = 500,
  workers = TRUE,
  n_sample = 1000,
  n_threads = NULL,
  compiled_compare = FALSE,
  adaptive_proposal = NULL,
  mcmc_path = NULL,
  verbose = TRUE
)

Arguments

`short_run`	Logical, indicating if this is a debug run. This will use freer particles, mcmc steps and a small sample
`n_chains`	The number of chains to run
`deterministic`	Logical, indicating if the model to fit to data is run deterministically or stochastically
`multiregion`	Logical, indicating if we are fitting multiple regions at once (in which case even the deterministic model may benefit from multithreading).
`rt`	Logical, indicating if we are calculating Rt trajectories or not. Default is TRUE
`severity`	Logical, indicating if we are outputting severity trajectories (e.g. IFR, IHR, HFR). Default to FALSE.
`intrinsic_severity`	Logical, indicating if we are calculating intrinsic severity (e.g. IFR, IHR, HFR). Default to FALSE.
`simulate`	Logical, indicating if we are outputting a simulate object for onward simulation
`demography`	Logical, indicating if we are outputting model demography - admissions and deaths by age
`date_restart`	Optionally, dates save restart data in the pmcmc (see mcstate::pmcmc
`n_particles`	number of particles to be used in particle filter if `short_run = FALSE`
`n_mcmc`	number of steps to be used in PMCMC if `short_run = FALSE`
`burnin`	number of steps out of `n_mcmc` to be used as a burn-in in PMCMC if `short_run = FALSE`
`workers`	Logical, indicating if we should enable workers. If `TRUE`, then a number of workers between 1 and 4 will be used depending on `n_chains` and the detected number of cores.
`n_sample`	number of steps to retain (across all chains) if `short_run = FALSE`
`n_threads`	Explicit number of threads, overriding detection by spim_control_cores
`compiled_compare`	Use a compiled compare function (rather than the R version). This can speed things up with the deterministic models in particular.
`adaptive_proposal`	Control the adaptive proposal. By default this is disabled (value of `NULL` or `FALSE`). This can only be enabled for determinsitic models. Pass either `TRUE` here or the results from `mcstate::adaptive_proposal_control()`
`mcmc_path`	Path to store the mcmc results in
`verbose`	Logical, indicating if we should print information about the parallel configuration