Description Usage Arguments Details Value Note Author(s) References See Also Examples
A dose response curve is produced for Electron Spin Resonance measurements using an additive dose protocol.
1 2 3 |
input.data |
|
model |
|
fit.weights |
|
algorithm |
|
mean.natural |
|
bootstrap |
|
bootstrap.replicates |
|
plot |
|
... |
further arguments |
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))
Bootstrap
If bootstrap = TRUE
the function generates
bootstrap.replicates
replicates of the input data for nonparametric
ordinary bootstrapping (resampling with replacement). For each bootstrap
sample a dose response curve is constructed by fitting the chosen function
and the equivalent dose is calculated. The distribution of bootstrapping
results is shown in a histogram, while a qqnorm
plot is
generated to give indications for (non-)normal distribution of the data.
Returns terminal output and a plot. In addition, a list is returned containing the following elements:
output |
data frame containing the De (De, De Error, D01 value). |
fit |
|
This function 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.
Bootstrap
While a higher number of replicates (bootstrap
samples) is desirable, it is also increasingly computationally intensive.
Christoph Burow, University of Cologne (Germany) Who wrote it
Efron, B. & Tibshirani, R., 1993. An Introduction to the
Bootstrap. Chapman & Hall.
Davison, A.C. & Hinkley, D.V., 1997.
Bootstrap Methods and Their Application. Cambridge University Press.
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.
plot
, nls
, lm
,
link{boot}
1 2 3 4 5 | ##load example data
data(ExampleData.De, envir = environment())
##plot ESR sprectrum and peaks
fit_DRC(input.data = ExampleData.De, fit.weights = 'prop')
|
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