winsrch_optim: Find the optimal half-window width combination

Description

Find the optimal half-window width combination to use for weighted regression.

Usage

winsrch_optim(dat_in, ...)
# S3 method for default
winsrch_optim(
  dat_in,
  wins_in = NULL,
  control = list(factr = 1e+07, parscale = c(1, 10, 1)),
  lower = c(0.1, 1, 0.1),
  upper = c(2, 15, 2),
  ...
)

Value

Some stuff

Arguments

dat_in: input data object to use with weighted regression
...: arguments passed to wrtdscv, wrtds, or getwts
wins_in: starting list of window weights for initializing the search algorithm
control: A list of control parameters passed to optim (see details in optim help file). The value passed to factr controls the convergence behavior of the "L-BFGS-B" method. Values larger than the default will generally speed up the optimization with a potential loss of precision. parscale describes the scaling values of the parameters.
lower: vector of minimum half-window widths to evaluate
upper: vector of maximum half-window widths to evaluate

Details

This function uses optim to minimize the error returned by wrtdscv for a given window combination. The search algorithm uses the limited-memory modification of the BFGS quasi-Newton method to impose upper and lower limits on the optimization search. These limits can be changed using the lower and upper arguments.

Examples

Run this code

if (FALSE) {
# setup parallel backend
library(doParallel)
ncores <- detectCores() - 1  
registerDoParallel(cores = ncores)

# run search function - takes a while
res <- winsrch_optim(tidobjmean)
}