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
Returns
Some stuff
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
## Not run:# setup parallel backendlibrary(doParallel)ncores <- detectCores()-1registerDoParallel(cores = ncores)# run search function - takes a whileres <- winsrch_optim(tidobjmean)## End(Not run)