Calculating and selecting a series of equivalent doses in a batch mode according to the single aliquot regenerative-dose (SAR) method (Murray and Wintle, 2000).
calSARED(obj_analyseBIN, model = "gok", origin = FALSE,
errMethod = "sp", nsim = 500, 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, calED.method = NULL, rseED.up = NULL,
use.se = TRUE, outpdf = NULL, outfile = NULL)
list(required): an object of S3 class "analyseBIN" produced by function analyseBINdata or as_analyseBIN
logical(with default): logical value indicating if the growth curve should be forced to pass the origin
integer(with default): desired number of randomly simulated equivalent dose obtained by Monte Carlo simulation
integer(optional): regenerative doses that will not be used during the fitting.
For example, if nofit.rgd=6
then the sixth regenerative dose will not be used during growth curve fitting
logical(with default): logical value indicating if aliquot (grain) with Tn below 3 sigma BG should be rejected
numeric(optional): lower limit on ratio of initial Tn signal to BG
numeric(optional): upper limit on relative standard error of Tn in percent
numeric(optional): lower limit on fast ratio of Tn
vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio 1,
Example: rcy1.range=c(0.9,1.1)
vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio 2
vector(optional): a two-element vector indicating the lower and upper limits on recycling ratio 3
numeric(optional): upper limit on recuperation 1 (i.e., ratio of the sensitivity-corrected zero-dose signal to natural-dose signal) in percent
numeric(optional): upper limit on recuperation 2 (i.e., ratio of the sensitivity-corrected zero-dose signal to maximum regenerative-dose signal) in percent
numeric(optional): upper limit on figure of merit (FOM) values of growth curves in percent
numeric(optional): upper limit on reduced chi-square (RCS) values of growth curves
character(optional): method used for equivalent dose calculation, i.e.,
"Interpolation"
or "Extrapolation"
numeric(optional): upper limit on the relative standard error of equivalent dose in percent
logical(with default): logical value indicating if standard errors of values should be used during application of rejection criteria
character(optional): if specified, results of SAR equivalent dose calculation will be written to a PDF file named "outpdf"
and saved to the current work directory
character(optional): if specified, SAR equivalent doses related quantities will be written
to a CSV file named "outfile"
and saved to the current work directory
Return an invisible list that contains the following elements:
a list containing optimized parameters of growth curves of calculated (selected) SAR equivalent doses
values and standard errors of Tn of calculated (selected) SAR equivalent doses
sensitivity-corrected natural-dose signals and associated standard errors used for SAR equivalent dose calculation
calculated (selected) SAR equivalent doses and associated standard errors
68 percent (one sigma) and 95 percent (two sigma) confidence intervals of SAR equivalent doses
aliquot (grain) ID of calculated (selected) SAR equivalent doses
a summary of the SAR equivalent dose calculation
Duller GAT, 2016. Analyst (v4.31.9), User Mannual.
Murray AS, Wintle AG, 2000. Luminescence dating of quartz using improved single-aliquot regenerative-dose protocol. Radiation Measurements, 32(1): 57-73.
Wintle AG, Murray AS, 2006. A review of quartz optically stimulated luminescence characteristics and their relevance in single-aliquot regeneration dating protocols. Radiation Measurements, 41(4): 369-391.
# NOT RUN {
data(BIN)
obj_pickBIN <- pickBINdata(BIN, Position=c(2,4,6,8,10), Grain=0,
LType="OSL", view=FALSE)
obj_analyseBIN <- analyseBINdata(obj_pickBIN, nfchn=3, nlchn=20)
res_SARED <- calSARED(obj_analyseBIN, model="exp", origin=FALSE)
# plot(res_SARED$Tn[,1], res_SARED$sarED[,1], xlab="Tn", ylab="ED (<Gy>|<s>)")
# }
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