pickSARdata {numOSL}

SAR data set selection

Description

Selecting SAR data sets (growth curves) in a batch model according to specified rejection criteria.

Usage

pickSARdata(obj_analyseBIN, model = "gok", origin = FALSE, 
            weight = TRUE, trial = TRUE, nofit.rgd = NULL, 
            Tn.above.3BG = TRUE, TnBG.ratio.low = NULL, 
            rseTn.up = NULL, FR.low = NULL, rcy1.range = NULL, 
            rcy2.range = NULL, rcy3.range = NULL, 
            rcp1.up = NULL, rcp2.up = NULL, fom.up = NULL, 
            rcs.up = NULL, use.se = TRUE, norm.dose = NULL, 
            outpdf = NULL, outfile = NULL)

Arguments

obj_analyseBIN

list(required): an object of S3 class "analyseBIN" produced by
function analyseBINdata or as_analyseBIN

model

character(with default): model used for growth curve fitting, see fitGrowth for available models

origin

logical(with default): logical value indicating if the growth curve should be forced to pass the origin

weight

logical(with default): logical value indicating if the growth curve should be fitted using a weighted procedure, see function fitGrowth for details

trial

logical(with default): logical value indicating if the growth curve should be fitted using other models if the given model fails, see function fitGrowth for details

nofit.rgd

integer(optional): regenerative doses that will not be used during the fitting. For example, if nofit.rgd=2 then the second regenerative dose will not be used during growth curve fitting

Tn.above.3BG

logical(with default): logical value indicating if aliquot (grain) with Tn below 3 sigma BG should be rejected

TnBG.ratio.low

numeric(optional): lower limit on ratio of initial Tn signal to BG

rseTn.up

numeric(optional): upper limit on relative standard error of Tn in percent

FR.low

numeric(optional): lower limit on fast ratio of Tn

rcy1.range

vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio 1, Example: rcy1.range=c(0.9,1.1)

rcy2.range

vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio 2

rcy3.range

vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio 3

rcp1.up

numeric(optional): upper limit on recuperation 1 (i.e., ratio of the
sensitivity-corrected zero-dose signal to natural-dose signal) in percent

rcp2.up

numeric(optional): upper limit on recuperation 2 (i.e., ratio of the
sensitivity-corrected zero-dose signal to maximum regenerative-dose signal)
in percent

fom.up

numeric(optional): upper limit on figure of merit (FOM) values of growth curves in percent

rcs.up

numeric(optional): upper limit on reduced chi-square (RCS) values of growth curves

use.se

logical(with default): logical value indicating if standard errors of values should be used during application of rejection criteria

norm.dose

numeric(optional): dose value used for SAR data set re-normalisation, for example, if norm.dose=100, then sensitivity-corrected signal for Redose=100 obtained through growth curve fitting will be used to re-normalise a SAR data set

outpdf

character(optional): if specified, results of growth curve fitting will be written to a PDF file named "outpdf" and saved to the current work directory

outfile

character(optional): if specified, SAR data related quantities will be written to a CSV file named "outfile" and saved to the current work directory

Value

Return an invisible list that contains the following elements:

LMpars

a list containing optimized parameters of growth curves of selected SAR data sets

SARdata

a data.frame containing selected SAR data sets

norm.SARdata

a data.frame containing re-normalised SAR data sets,
it returns NULL if norm.dose=NULL

agID

aliquot or grain ID (i.e., c("NO","Position","Grain")) of selected SAR data

summary.info

a summary of the SAR data selection

See Also

analyseBINdata; fitGrowth; lsNORM; calSARED

Examples

 # Not run.
 # data(BIN)
 # obj_pickBIN <- pickBINdata(BIN, Position=1:48, Grain=0, 
 #                            LType="OSL", view=FALSE)
 # obj_analyseBIN <- analyseBINdata(obj_pickBIN, nfchn=3, nlchn=20) 
 # pickSARdata(obj_analyseBIN, model="gok", fom.up=3, outpdf="SARdata")