calc_DePlateau: Fit a dose response curve to ESR data and create a DE-DEmax...

In tzerk/ESR: Package for Electron Spin Resonance Dating Data Analysis

Description

This function repeatedly fits a single saturating exponential to ESR data and calculates the De while removing the highest datapoint datapoint after each iteration. It then creates a DE-DEmax-Plot after Schellmann & Radtke (2001) where the DE is plotted against the number of datapoints used for fitting.

Usage

calc_DePlateau(input.data, min.DosePoints = 5, fit.weights = "equal",
  model = "EXP", mean.natural = FALSE, show.grid = TRUE,
  output.console = TRUE, ...)

Arguments

input.data	data.frame (required): data frame with two columns for x=Dose, y=ESR.intensity. Optional: a third column containing individual ESR intensity errors can be provided.
min.DosePoints	integer (with default): minimum number of datapoints used for fitting the single saturating exponential.
fit.weights	logical (with default): option whether the fitting is done with equal weights ('equal') or weights proportional to intensity ('prop'). If individual ESR intensity errors are provided, these can be used as weights by using 'error'.
model	character (with default): Currently implemented models: single-saturating exponential ("EXP"), linear ("LIN").
mean.natural	logical (with default): If there are repeated measurements of the natural signal should the mean amplitude be used for fitting?
show.grid	logical (with default): show horizontal grid lines in plots (TRUE/FALSE)
output.console	logical (with default): plot console output (TRUE/FALSE)
...	further arguments passed to plot and par.

Details

Fitting methods

For fitting of the dose response curve the nls function with the port algorithm is used. A single saturating exponential in the form of

y = a*(1-exp(-(x+c)/b))

is fitted to the data. Parameters b and c are approximated by a linear fit using lm.

Fit weighting

If 'equal' all datapoints are weighted equally. For 'prop' the datapoints are weighted proportionally by their respective ESR intensity:

fit.weights = 1/intensity/(sum(1/intensity))

If individual errors on ESR intensity are available, choosing 'error' enables weighting in the form of:

fit.weights = 1/error/(sum(1/error))

Value

Returns terminal output and a plot. In addition, a list is returned containing the following elements:

output

data frame containing the De (datapoints n, De, De.Error, max.Dose).

Note

Fitting of the dose response curve using fit_DRC is largely derived from the plot_GrowthCurve function of the 'Luminescence' package by Kreutzer et al. (2012).

Fitting methods
Currently, only fitting of a single saturating exponential is supported. Fitting of two exponentials or an exponential with a linear term may be implemented in a future release.

Author(s)

Christoph Burow, University of Cologne (Germany) Who wrote it

References

Galbraith, R.F. & Roberts, R.G., 2012. Statistical aspects of equivalent dose and error calculation and display in OSL dating: An overview and some recommendations. Quaternary Geochronology, 11, pp. 1-27.

Kreutzer, S., Schmidt, C., Fuchs, M.C., Dietze, M., Fischer, M., Fuchs, M., 2012. Introducing an R package for luminescence dating analysis. Ancient TL, 30 (1), pp 1-8.

See Also

plot, nls, lm, fit_DRC

Examples

## Not run: 
##load example data
data(ExampleData.De, envir = environment())

#calculate and plot De-Dmax Plateau
calc_DePlateau(input.data = ExampleData.De,
               min.DosePoints = 5, 
               fit.weights = 'prop', 
               show.grid = TRUE, 
               output.console = FALSE)

## End(Not run)

tzerk/ESR documentation built on May 20, 2019, 1:12 p.m.