Assess timeseries for trends and status — run

Fits a model to each timeseries, test for any temporal trend and compare with thresholds. Need to add a lot more in details.

Usage

run_assessment(
  ctsm_ob,
  subset = NULL,
  AC = NULL,
  get_AC_fn = NULL,
  recent_trend = 20L,
  parallel = FALSE,
  extra_data = NULL,
  control = list(),
  ...
)

Arguments

ctsm_ob: A HARSAT object resulting from a call to create_timeSeries
subset: An optional vector specifying which timeseries are to be assessed. Might be used if the assessment is to be done in chunks because of size, or when refitting a timeseries model which has not converged. An expression will be evaluated in the timeSeries component of ctsm_ob; use 'series' to identify individual timeseries.
AC: A character vector identifying the thresholds to be used in status assessments. These should be in the threshold reference table. Defaults to NULL; i.e. no thresholds are used.
get_AC_fn: An optional function that overrides get_AC_default. See details (which need to be written).
recent_trend: An integer giving the number of years which are used in the assessment of recent trends. For example, a value of 20 (the default) consider trends in the last twenty year.
parallel: A logical which determines whether to use parallel computation; default = FALSE.
extra_data: A named list used to pass additional data to specific assessment routines. At present it is only used for imposex assessments, where it passes two data frames called VDS_estimates and VDS_confidence_limits. Defaults to NULL, This argument will be generalised in the near future, so expect it to change.
control: A list of control parameters that allow the user to modify the way the assessment is run. At present, these only include parameters involved in post-hoc power calculations, but it is intended to move other structures such as recent_trend here. See details (which need to be written).
...: Extra arguments which are passed to assessment_engine. See details (which need to be written).