Learn R Programming

numOSL (version 2.0)

pickSARED: Single aliquot regenerative-dose (SAR) equivalent dose record selection

Description

Extracting SAR equivalent dose records according to certain criteria (recycling ratio, recuperation, figure-of-merit and reduced-chi-square values of fitted growth curves).

Usage

pickSARED(obj, rsdED.limit = NULL, rcy.interval = NULL, rcp1.limit = NULL, rcp2.limit = NULL, method = NULL, fom.limit = NULL, rcs.limit = NULL, outfile = NULL)

Arguments

obj
list(required): an object of S3 class "calSARED", which is produced by function calSARED
rsdED.limit
double(optional): upper limit on the relative standard error of equivalent dose in percent
rcy.interval
vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio, for example, rcy.interval=c(0.9,1.1)
rcp1.limit
double(optional): upper limit on recuperation1 (i.e., the ratio of standardised zero regenerative dose signal to standardised natural dose signal) in percent
rcp2.limit
double(optional): upper limit on recuperation2 (i.e., the ratio of standardised zero regenerative dose signal to maximum standardised regenerative dose signal) in percent
method
character(optional): method used for SAR equivalent dose calculation (interpolation or extrapolation)
fom.limit
double(optional): upper limit on figure-of-merit (FOM) values of fitted growth curves in percent
rcs.limit
double(optional): upper limit on reduced-chi-square (RCS) values of fitted growth curves
outfile
character(optional): if specified, selected SAR equivalent doses and relevant quantities will be written to a CSV file named "outfile" and saved to the current work directory

Value

Return a list that contains the following elements:
sarED
selected SAR equivalent doses
reject.NO
rejected Grain.NO

See Also

calSARED; pickSARdata; select

Examples

Run this code
  # Do not run.
  # data(SARdata)
  # res <- calSARED(SARdata, model="gok", trace=TRUE)
  # pickSARED(res, rcy.interval=c(0.9, 1.1))

Run the code above in your browser using DataLab