trim_workhorse function

TRIM workhorse function

trim_workhorse(
  count,
  site,
  year,
  month,
  weights,
  covars,
  model,
  changepoints,
  overdisp,
  serialcor,
  autodelete,
  stepwise,
  covin = list(),
  constrain_overdisp = 1,
  conv_crit = 1e-05,
  max_iter = 200,
  alpha_method = 1,
  debug = FALSE
)

Arguments

• count: a numerical vector of count data.
• site: a numerical vector time points for each count data point.
• year: an numerical vector time points for each count data point.
• month: vector of month data.
• weights: a numerical vector of weights.
• covars: an optional data frame with covariates
• model: a model type selector
• changepoints: a numerical vector change points (only for Model 2)
• overdisp: a flag indicating of overdispersion has to be taken into account.
• serialcor: a flag indication of autocorrelation has to be taken into account.
• covin: a list of variance-covariance matrices; one per pseudo-site.
• constrain_overdisp: control constraining overdispersion
• conv_crit: convergence criterion.
• max_iter: maximum number of iterations allowed.
• alpha_method: choose between a more precise (1) or robust (2) method to estimate site parameters alpha.

Returns

a list of class trim, that contains all output, statistics, etc. Usually this information is retrieved by a set of postprocessing functions