numOSL (version 1.8)

fastED: Fast-component equivalent dose calculation

Description

Estimating a fast-component equivalent dose using decay curves obtained from a SAR sequence.

Usage

fastED(Sigdata, Redose, ncomp = 2, constant = TRUE,  
       control.args = list(), typ = "cw", nstart = 100, 
       upb = 0.5, ErrorMethod = c("mc","sp"), nsim = 1000,
       model = NULL, origin = NULL, weight = c("g","d","b","n"))

Arguments

Sigdata

matrix(required): a series of decay curves stored column by column, the structure is different from that in function analyst, here the first column represents stimulation time v

Redose

vector(required): regenerative dose values. Example, Redose=c(1,2,3,4,0,1)

ncomp

integer(with default): number of components to be decomposed

constant

logical(with default): subtract a constant component or not

control.args

list(with default): arguments used by the differential evolution algorithm, see function decomp for details

typ

character(with default): type of an OSL decay curve, only CW-OSL decay curve can be analyzed currently

nstart

integer(with default): maximum number of trials used for initializing the non-linear growth curve, see function fitGrowth for details

upb

double(with default): upper limit on b value (i.e., the reciprocal of the saturating dose), see function fitGrowth for details

ErrorMethod

character(with default): a method used for assessing the standard error of an equivalent dose, default ErrorMethod="mc", see function calED for details

nsim

integer(with default): maximum number of simulations if a Monte Carlo method is applied to assessing the standard error of an equivalent dose

model

character(optional): model used for fitting the growth curve, see function fitGrowth for available models. The procedure will find an optimal model between "line" and

origin

logical(optional): force the fast-component growth curve to pass the origin or not. The procedure will choose whether pass the origin or not automatically if origin=NULL

weight

character(with default): type of curves to be fitted by a weighted procedure, "g" means applying a weighted procedure to fitting the growth curve, "d" means applying a weigthed procedure to f

Value

• Return a list containing the following elements:
• pars
  estimated decay rates and trapped electrons for each decay curve
• decayRateMat
  decay rates for each decay curve stored in a matrix
• Curvedata
  data used for constructing the fast-component growth curve
• Ltx
  sensitivity-corrected natural OSL for the fast-component and associated standard error
• model
  fitting model of the growth curve
• LMpars
  optimizaed parameters of the growth curve
• value
  minimized objective of the growth curve
• ED
  fast-component equivalent dose and its standard error
• RecyclingRatio
  fast-component recycling ratio
• Recuperation
  fast-component recuperation

Details

Function fastED is used to estimate a fast-component equivalent dose using a data set obtained from a 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-component are used to construct a growth curve to estimate a fast-component equivalent dose. See function decomp, fitGrowth, and calED for more details concerning decay curve decomposition, growth curve fitting, and equivalent dose calculation.

References

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.

See Also

analyst; calED; decomp; fitGrowth

Examples

data(Signaldata)
 # Use only the first two regenerative dose values. 
 fastED(Signaldata$cw[,-(8:15)],Redose=c(80,160)*0.13,model="line",
        control.args=list(factor=5,maxiter=50),origin=TRUE)
 # Use all regenerative dose values (except the zero-dose).
 # fastED(Signaldata$cw[,c(-12,-13)],Redose=c(80,160,240,320,80)*0.13,
 #        ncomp=3,constant=FALSE)