trim_refine: TRIM stepwise refinement

In rtrim: Trends and Indices for Monitoring Data

Description

TRIM stepwise refinement

Usage

trim_refine(
  count,
  site,
  year,
  month,
  weights,
  covars,
  model,
  changepoints,
  ...,
  premove = 0.2,
  penter = 0.15
)

Arguments

count	a numerical vector of count data.
site	a vector (numerical or factor) of site identifiers for each count data point.
year	a numerical vector of annual time points for each count data point.
month	an optional numerical vector of monthly time points.
weights	an optional numerical vector of weights.
covars	an optional list of covariates.
model	a model type selector.
changepoints	a numerical vector change points (only for Model 2)
premove	threshold probability for removal of parameters.
penter	threshold probability for re-introduction of parameters.

Value

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

rtrim documentation built on April 21, 2020, 5:06 p.m.