simulateAccount {demest} | R Documentation

## Create a synthetic demographic account

### Description

WARNING - THIS FUNCTION IS STILL UNDER DEVELOPMENT

### Usage

    simulateAccount(
      account,
      systemModels,
      datasets = list(),
      dataModels = list(),
      concordances = list(),
      weights = list(),
      dominant = c("Female", "Male"),
      usePriorPopn = TRUE,
      updateSystemModel = NULL,
      updateDataModel = NULL,
      updateInitialPopn = TRUE,
      probSmallUpdate = 0,
      scaleNoise = 0,
      filename = NULL,
      nBurnin = 1000,
      nSim = 1000,
      nChain = 4,
      nThin = 1,
      parallel = TRUE,
      nCore = NULL,
      outfile = NULL,
      nUpdateMax = 50,
      verbose = TRUE,
      useC = TRUE
    )

### Arguments

`account` | An object of class `DemographicAccount`, giving the initial values for the estimation of the account.
`systemModels` | A list of objects of class `SpecModel` specifying models for the demographic series.
`datasets` | A named list of objects of class `Counts`.
`dataModels` | A list of objects of class `SpecModel` specifying models for the datasets.
`concordances` | A named list of `concordances`, which are applied to the series in the account before they are supplied to the corresponding data model.
`weights` | A named list of `Counts` objects, providing weights for any Normal models among the system models.
`dominant` | Either `"Female"` (the default) or `"Male"`. Determines which sex is used to generate exposures in the system model for births.
`usePriorPopn` | Whether to take account of the prior model for population when inferring values for the account. Defaults to `TRUE`.
`updateSystemModel` | Names of any system models containing parameters that need to be estimated (as oppsed to simply drawn from the prior distribution) as part of the simulation.
`updateDataModel` | Names of any data models containing parameters that need to be estimated (as oppsed to simply drawn from the prior distribution) as part of the simulation.
`updateInitialPopn` | If `TRUE` (the default) population counts in the first year of the account are inferred as part of the overall estimation process. If `FALSE`, the values supplied for the first year are treated as error-free and never updated.
`probSmallUpdate` | Proportion of updates of components that are 'small', ie that only consist of exchanging values between two neighbouring Lexis triangles.
`scaleNoise` | Governs noise added to Metropolis-Hastings ratio. Should be non-zero only when trying to generate initial values. Currently experimental, and may change.
`filename` | The name of a file where output is collected.
`nBurnin` | Number of iteration discarded before recording begins.
`nSim` | Number of iterations carried out during recording.
`nChain` | Number of independent chains to use.
`nThin` | Thinning interval.
`parallel` | Logical. If `TRUE` (the default), parallel processing is used.
`nCore` | The number of cores to use, when `parallel` is `TRUE`. If no value supplied, defaults to `nChain`.
`outfile` | Where to direct the ‘stdout’ and ‘stderr’ connection output from the workers when parallel processing. Passed to function `[parallel]{makeCluster}`.
`nUpdateMax` | Maximum number of iterations completed before releasing memory. If running out of memory, setting a lower value than the default may help.
`verbose` | Logical. If `TRUE` (the default) a message is printed at the end of the calculations.
`useC` | Logical. If `TRUE` (the default), the calculations are done in C. Setting `useC` to `FALSE` may be useful for debugging.

[Package demest version 0.0.0.3.1 Index]