wtobjfun: An objective function to minimize plus weighted regression...

In fawda123/WtRegDO: Implement Weighted Regression on Dissolved Oxygen Time Series

An objective function to minimize plus weighted regression for finding optimal window widths

Description

An objective function to minimize plus weighted regression for finding optimal window widths

Usage

wtobjfun(
  wins,
  dat_in,
  tz,
  lat,
  long,
  metab_obs,
  strt = NULL,
  vls = c("meanPg", "sdPg", "anomPg", "meanRt", "sdRt", "anomRt"),
  parallel = F,
  progress = T
)

Arguments

wins	list of half-window widths to use in the order specified by wtfun (i.e., days, hours, tide height).
dat_in	input data frame
tz	chr string specifying timezone of location, e.g., 'America/Jamaica' for EST, no daylight savings, must match the time zone in dat_in$DateTimeStamp
lat	numeric for latitude of location
long	numeric for longitude of location (negative west of prime meridian)
metab_obs	A metab object returned by ecometab based on the observed DO time series in dat_in, used as comparison for the objective function
strt	a POSIXct object returned by Sys.time
vls	chr vector of summary evaluation object to optimize, see details for objfun
parallel	logical if regression is run in parallel to reduce processing time, requires a parallel backend outside of the function
progress	logical if progress saved to a txt file names 'log.txt' in the working directory

Value

A single numeric value to minimize, as output from objfun

See Also

objfun, winopt

Examples

## Not run: 

library(foreach)
library(doParallel)

data(SAPDC)

tz <- 'America/Jamaica'
lat <- 31.39
long <- -81.28

metobs <- ecometab(SAPDC, DO_var = 'DO_obs', tz = tz, lat = lat, long = long)

ncores <- detectCores()
cl <- makeCluster(ncores)
registerDoParallel(cl)

wtobjfun(SAPDC, tz = tz, lat = lat, long = long, metab_obs = metobs, strt = Sys.time(),
   wins = list(6, 6, 0.5), parallel = T)

stopCluster(cl)

## End(Not run)

fawda123/WtRegDO documentation built on March 18, 2024, 9:04 p.m.