numOSL (version 1.6)

calED: Calculating an equivalent dose value and estimating its standard error

Description

Calculating an equivalent dose value and assessing its standard error using methods described in Duller (2007).

Usage

calED(Curvedata, Ltx, model = c("line","exp","lexp","dexp"), 
      origin = FALSE, nstart = 100, upb = 0.5, ErrorMethod = c("mc","sp"),
      nsim = 1000, plot = TRUE, outfile = NULL)

Arguments

Curvedata

matrix(required): three columns, i.e., regenerative doses, standardised OSL signals, and standard errors of standardised OSL signals

Ltx

vector or matrix(required): natural standardised OSL signal(s) and standard error(s), see details

model

character(with default): a fitting model, default model="line", see fitGrowth for available models

origin

logical(optional): force the fitting to pass the origin or not

nstart

numeric(with default): the maximum number of attempts of initializing the non-linear growth curve fitting, see function fitGrowth for details

upb

numeric(with default): the upper limit on b value (i.e., the reciprocal of the saturating dose), initial b value is generated uniformly from the space (0,upb), see function

ErrorMethod

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

nsim

numeric(with default): the allowed maximum number of simulations when applying a Monte Carlo method to assess the standard error of an equivalent dose

plot

logical(with default): draw a plot or not

outfile

character(with default): if specified, simulated ED values will be written to a file named "outfile" in ".csv" format and saved to the current work directory

Value

• Return an list that contains following elements:
• LMpars
  parameters and standard errors of the growth curve
• value
  the minimized chi-square value of the fitted growth curve
• fit.value
  observations and fitted values
• ED
  equivalent dose(s) and standard error(s)

Details

This function can be used for calculating a single ED value (if Ltx is a two-element vector) or a number of ED values using the "Standardised Growth Curve" method (if Ltx is a two-column multi-row matrix). Standard error of an equivalent dose can be assessd using two method outlined by Duller (2007): (a) "sp": a simple transformation of s(Lx/Tx) to s(ED); (b) "mc": a Monte Carlo method Interpolation is performed using a combination of golden section search and successive parabolic interpolation (available at http://www.netlib.org/fmm/fmin.f). See function fitGrowth for more details.

References

Duller GAT, 2007. Assessing the error on equivalent dose estimates derived from single aliquot regenerative dose measurements. Ancient TL, 25: 15-24.

Roberts HM, Duller GAT, 2004. Standardised growth curves for optical dating of sediment using multiple-grain aliquots. Radiation Measurements, 38: 241-252.

See Also

analyst; fastED; fitGrowth

Examples

# Calculating a number of ED values (a SGC method).
  ltx1<-c(0.032,1.61,2.55,3.21,3.87,0.031,1.55) # Lx/Tx for the first aliquot
  ltx2<-c(0.025,1.44,2.47,3.35,4.17,0.033,1.47) # Lx/Tx for the second aliquot
  ltx3<-c(0.027,1.51,2.68,3.52,4.41,0.021,1.39) # Lx/Tx for the third aliquot
  ltx4<-c(0.018,1.71,2.28,3.81,4.03,0.017,1.62) # Lx/Tx for the four aliquot
  ltx5<-c(0.026,1.49,1.99,3.43,4.17,0.015,2.01) # Lx/Tx for the five aliquot
  ltx<-cbind(ltx1,ltx2,ltx3,ltx4,ltx5)
  ltx<-cbind(apply(ltx,MARGIN=1,mean),
             apply(ltx,MARGIN=1,sd))  # means and standard deviations
  redose<-c(0,18,36,54,72,0,18)       # the same ReDose for the five aliquots
  Curvedata<-data.frame(redose,ltx)
  Ltx<-cbind(c(0.5,1.0,1.8,2.3,2.8,3.1,3.6,4.0),rep(0.1,8))         
  calED(Curvedata,Ltx,model="exp",origin=FALSE) # fitting y=a*(1-exp(-b*x))+c