trim_workhorse: TRIM workhorse function
In rtrim: Trends and Indices for Monitoring Data

trim_workhorse

R Documentation

TRIM workhorse function

Description

TRIM workhorse function

Usage

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.