controlMethod: Control parameters for regression

In singleRcapture: Single-Source Capture-Recapture Models

Control parameters for regression

Description

controlMethod constructs a list with all necessary control parameters for regression fitting in estimatePopsizeFit and estimatePopsize.

Usage

controlMethod(
  epsilon = 1e-08,
  maxiter = 1000,
  verbose = 0,
  printEveryN = 1L,
  coefStart = NULL,
  etaStart = NULL,
  optimMethod = "Nelder-Mead",
  silent = FALSE,
  optimPass = FALSE,
  stepsize = 1,
  checkDiagWeights = TRUE,
  weightsEpsilon = 1e-08,
  momentumFactor = 0,
  saveIRLSlogs = FALSE,
  momentumActivation = 5,
  criterion = c("coef", "abstol", "reltol")
)

Arguments

epsilon	a tolerance level for fitting algorithms by default 1e-8.
maxiter	a maximum number of iterations.
verbose	a numeric value indicating whether to trace steps of fitting algorithm for IRLS fitting method different values of verbose give the following information: 1 – Returns information on the number of current iteration and current log-likelihood. 2 – Returns information on vector of regression parameters at current iteration (and all of the above). 3 – Returns information on reduction of log-likelihood at current iteration (and all of the above). 4 – Returns information on value of log-likelihood function gradient at current iteration (and all of the above). 5 – Returns information on convergence criterion and values that are taken into account when considering convergence (and all of the above). if optim method was chosen verbose will be passed to stats::optim() as trace.
printEveryN	an integer value indicating how often to print information specified in verbose, by default set to 1.
coefStart, etaStart	initial parameters for regression coefficients or linear predictors if NULL. For IRLS fitting only etaStart is needed so if coefStart is provided it will be converted to etaStart, for optim fitting coefStart is necessary and argument etaStart will be ignored.
optimMethod	a method of stats::optim() used "Nelder-Mead" is the default .
silent	a logical value, indicating whether warnings in IRLS method should be suppressed.
optimPass	an optional list of parameters passed to stats::optim(..., control = optimPass) if FALSE then list of control parameters will be inferred from other parameters.
stepsize	only for IRLS, scaling of updates to beta vector lower value means slower convergence but more accuracy by default 1. In general if fitting algorithm fails lowering this value tends to be most effective at correcting it.
checkDiagWeights	a logical value indicating whether to check if diagonal elements of working weights matrixes in IRLS are sufficiently positive so that these matrixes are positive defined. By default TRUE.
weightsEpsilon	a small number to ensure positive definedness of weights matrixes. Only matters if checkDiagWeights is set to TRUE. By default 1e-8.
momentumFactor	an experimental parameter in IRLS only allowing for taking previous step into account at current step, i.e instead of updating regression parameters as: \mjsdeqn\boldsymbol\beta_(a) = \boldsymbol\beta_(a-1) + \textstepsize \cdot \textstep_(a) the update will be made as: \mjsdeqn \boldsymbol\beta_(a) = \boldsymbol\beta_(a-1) + \textstepsize \cdot (\textstep_(a) + \textmomentum\cdot\textstep_(a-1))
saveIRLSlogs	a logical value indicating if information specified in verbose should be saved to output object, by default FALSE.
momentumActivation	the value of log-likelihood reduction bellow which momentum will apply.
criterion	a criterion used to determine convergence in IRLS, multiple values may be provided. By default c("coef", "abstol").

Value

List with selected parameters, it is also possible to call list directly.

Author(s)

Piotr Chlebicki, Maciej Beręsewicz \loadmathjax

See Also

estimatePopsize() estimatePopsizeFit() controlModel() controlPopVar()

singleRcapture documentation built on April 4, 2025, 1:43 a.m.