trim_estimate: TRIM estimation function
In rtrim: Trends and Indices for Monitoring Data

TRIM estimation function

trim_estimate(
  count,
  site,
  year,
  month,
  weights,
  covars,
  model,
  changepoints,
  overdisp,
  serialcor,
  autodelete,
  stepwise,
  covin,
  verbose = FALSE,
  ...
)

`count`	a numerical vector of count data.
`site`	an integer/numerical/character/factor vector of site identifiers for each count data point
`year`	an integer/numerical vector time points for each count data point.
`month`	an optional integer/character/factor vector of months for each count data point.
`weights`	an optional numerical vector of weights.
`covars`	an optional data frame withcovariates
`model`	a model type selector (1, 2 or 3)
`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.
`autodelete`	a flag indicating auto-deletion of changepoints with too little observations.
`stepwise`	a flag indicating stepwise refinement of changepoints is to be used.
`covin`	a list of variance-covariance matrices; one per pseudo-site.
`verbose`	flag to enable addtional output during a single run.