Estimating a fast-, medium-, or slow-component equivalent dose using decay curves obtained from the single aliquot regenerative-dose (SAR) method.
fastED(Sigdata, Redose, delay.off = c(0,0), ncomp = 2,
constant = TRUE, compIDX = 1, control.args = list(),
typ = "cw", model = "gok", origin = FALSE, errMethod = "sp",
nsim = 500, weight.decomp = FALSE, weight.fitGrowth = TRUE,
trial = TRUE, nofit.rgd = NULL, outpdf = NULL, log = "x",
lwd = 2, test.dose = NULL, agID = NULL)Return an invisible list containing the following elements:
a list containing optimized parameters of successfully fitted decay curves
data sets used for building the fast-, medium-, or slow-component growth curve
sensitivity-corrected natural-dose fast-, medium-, or slow-component signal and its standard error
optimizaed parameters for the fast-, medium-, or slow-component growth curve
minimized objective for the fast-, medium-, or slow-component growth curve
average fit error for the fast-, medium-, or slow-component growth curve
reduced chi-square value for the fast-, medium-, or slow-component growth curve
figure of merit value for the fast-, medium-, or slow-component growth curve in percent
method used for calculating the fast-, medium-, or slow-component equivalent dose, i.e., "Interpolation" or "Extrapolation"
randomly simulated fast-, medium-, or slow-component equivalent doses
fast-, medium-, or slow-component equivalent dose and its standard error
68 percent and 95 percent confidence interval of the fast-, medium-, or slow-component equivalent dose
the first fast-, medium-, or slow-component recycling ratio and its standard error
the second fast-, medium-, or slow-component recycling ratio and its standard error
the third fast-, medium-, or slow-component recycling ratio and its standard error
the first fast-, medium-, or slow-component recuperation (i.e., ratio of the sensitivity-corrected zero-dose signal to natural-dose signal) and its standard error in percent
the second fast-, medium-, or slow-component recuperation (i.e., ratio of the sensitivity-corrected zero-dose signal to the maximum regenerative-dose signal) and its standard error in percent
matrix(required): a series of decay curves stored in a matrix column by column, the first column denotes stimulation time values, see details.
Data structure of this kind can be obtained using function pickBINdata by setting argument force.matrix=TRUE, see examples
vector(required): regenerative dose values. Example: Redose=c(1,2,3,4,0,1)
vector(with default): a two-elment vector indicating the "Delay" and "Off"
values of the decay curves, i.e., delay.off[1]=Delay,delay.off[2]=Off
integer(with default): number of components to be decomposed
logical(with default): logical value indicating if a constant background should be subtracted from the decay curve, see function decomp for details
integer(with default): index of the component to be extracted. For example, compIDX=1 and compIDX=2 indicate respectively that
the fast- and medium-component signals will be used to calculate the equivalent dose. The index should not exceed the number of components to be decomposed
list(with default): arguments used in the differential evolution algorithm, see function decomp for details
character(with default): type of an OSL decay curve, only CW-OSL decay curve can be analyzed currently
character(with default): model used for growth curve fitting, see function
fitGrowth for available models
logical(with default): logical value indicating if the growth curve should be forced to pass the origin
character(with default): method used for equivalent dose error assessment. See function calED for details
integer(with default): desired number of randomly simulated equivalent dose obtained by Monte Carlo simulation
character(with default): logical value indicating if the decay curve should be fitted using a weighted procedure, see function decomp for details
character(with default): logical value indicating if the growth curve should be fitted using a weighted procedure, see function fitGrowth for details
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
integer(optional): regenerative doses that will not be used during the fitting.
For example, if nofit.rgd=1 then the first regenerative dose will not be used during fast-, medium-, or slow-component growth curve fitting
character(optional): if specified, results of fast-, medium-, or slow-component equivalent dose calculation will be written to a PDF file
named "outpdf" and saved to the current work directory
character(with default): a character string which contains "x" if the x axis is to be logarithmic, "y" if the y axis is to be logarithmic and "xy" or "yx" if both axes are to be logarithmic
numeric(with default): width of curves (lines)
numeric(optional): test dose of decay curves
vector(optional): a three-elemenet vector indicating aliquot (grain) ID, i.e.,
agID[1]=NO, agID[2]=Position, agID[3]=Grain
Function fastED is used to estimate a fast-, medium-, or slow-component equivalent dose using data sets obtained from the SAR protocol (Murray and Wintle, 2000). The routine trys to decompose a series of decay curves to a specified number of components, then the numbers of trapped electrons from the fast-, medium-, or slow-component will be used to construct the growth curve to estimate a fast-, medium-, or slow-component equivalent dose. See function decomp, fitGrowth, and calED for more details concerning decay curve decomposition, growth curve fitting, and equivalent dose calculation, respectively.
Argument Sigdata is a column-matrix made up with stimulation time values and a number of decay curves:
| Column.no | Description | I |
| Stimulation time values | II | Natural-dose signal values |
III | Test-dose signal values for the natural-dose | IV |
| The 1th Regenerative-dose signal values | V | Test-dose signal values for the 1th regenerative-dose |
VI | The 2th regenerative-dose signal values | VII |
| Test-dose signal values for the 2th regenerative-dose | ... | ... |
Li SH, Li B, 2006. Dose measurement using the fast component of LM-OSL signals from quartz. Radiation Measurements, 41(5): 534-541.
Murray AS, Wintle AG, 2000. Luminescence dating of quartz using improved single-aliquot regenerative-dose protocol. Radiation Measurements, 32(1): 57-73.
pickBINdata; Signaldata; fitGrowth; decomp; calED
### Example 1 (not run):
# data(Signaldata)
# fastED(Signaldata$cw,Redose=c(80,160,240,320,0, 80)*0.13,
# ncomp=3, constant=FALSE, compIDX=1, outpdf="fastED1")
# fastED(Signaldata$cw,Redose=c(80,160,240,320,0, 80)*0.13,
# ncomp=3, constant=FALSE, compIDX=2, outpdf="mediumED1")
# fastED(Signaldata$cw,Redose=c(80,160,240,320,0, 80)*0.13,
# ncomp=3, constant=FALSE, compIDX=3, outpdf="slowED1")
### Example 2 (not run):
# data(BIN)
# obj_pickBIN <- pickBINdata(BIN, Position=6, Grain=0,
# LType="OSL", force.matrix=TRUE)
# fastED(obj_pickBIN$BINdata[[1]], ncomp=2, constant=TRUE,
# Redose=c(100,200,300,400,0,100)*0.13, outpdf="fastED2")
Run the code above in your browser using DataLab