R/analyse_FadingMeasurement.R
analyse_FadingMeasurement.Rd
The function analysis fading measurements and returns a fading rate including an error estimation. The function is not limited to standard fading measurements, as can be seen, e.g., Huntley and Lamothe (2001). Additionally, the density of recombination centres (rho') is estimated after Kars et al. (2008).
analyse_FadingMeasurement( object, structure = c("Lx", "Tx"), signal.integral, background.integral, t_star = "half", n.MC = 100, verbose = TRUE, plot = TRUE, plot.single = FALSE, ... )
object | RLum.Analysis (required): input object with the measurement data. Alternatively, a list containing RLum.Analysis objects or a data.frame with three columns (x = LxTx, y = LxTx error, z = time since irradiation) can be provided. Can also be a wide table, i.e. a data.frame with a number of columns divisible by 3 and where each triplet has the before mentioned column structure. Please note: The input object should solely consists of the curve needed for the data analysis, i.e. only IRSL curves representing Lx (and Tx) If data from multiple aliquots are provided please see the details below with regard to Lx/Tx normalisation. The function assumes that all your measurements are related to one (comparable) sample. If you to treat independent samples, you have use this function in a loop. |
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structure | character (with default):
sets the structure of the measurement data. Allowed are |
signal.integral | vector (required):
vector with the limits for the signal integral.
Not required if a |
background.integral | vector (required):
vector with the bounds for the background integral.
Not required if a |
t_star | character (with default):
method for calculating the time elapsed since irradiation. Options are:
|
n.MC | integer (with default): number for Monte Carlo runs for the error estimation |
verbose | logical (with default): enables/disables verbose mode |
plot | logical (with default): enables/disables plot output |
plot.single | logical (with default):
enables/disables single plot mode, i.e. one plot window per plot.
Alternatively a vector specifying the plot to be drawn, e.g.,
|
... | (optional) further arguments that can be passed to internally used functions. Supported arguments:
|
An RLum.Results object is returned:
Slot: @data
OBJECT | TYPE | COMMENT |
fading_results | data.frame | results of the fading measurement in a table |
fit | lm | object returned by the used linear fitting function stats::lm |
rho_prime | data.frame | results of rho' estimation after Kars et al. (2008) |
LxTx_table | data.frame | Lx/Tx table, if curve data had been provided |
irr.times | integer | vector with the irradiation times in seconds |
Slot: @info
OBJECT | TYPE | COMMENT |
call | call | the original function call |
All provided output corresponds to the \(tc\) value obtained by this analysis. Additionally in the output object the g-value normalised to 2-days is provided. The output of this function can be passed to the function calc_FadingCorr.
Fitting and error estimation
For the fitting the function stats::lm is used without applying weights. For the
error estimation all input values, except tc
, as the precision can be considered as sufficiently
high enough with regard to the underlying problem, are sampled assuming a normal distribution
for each value with the value as the mean and the provided uncertainty as standard deviation.
Density of recombination centres
The density of recombination centres, expressed by the dimensionless variable rho', is estimated by fitting equation 5 in Kars et al. 2008 to the data. For the fitting the function stats::nls is used without applying weights. For the error estimation the same procedure as for the g-value is applied (see above).
Multiple aliquots & Lx/Tx normalisation
Be aware that this function will always normalise all Lx/Tx values by the Lx/Tx value of the
prompt measurement of the first aliquot. This implicitly assumes that there are no systematic
inter-aliquot variations in Lx/Tx values. If deemed necessary to normalise the Lx/Tx values
of each aliquot by its individual prompt measurement please do so before running
analyse_FadingMeasurement and provide the already normalised values for object
instead.
0.1.16
Kreutzer, S., Burow, C., 2021. analyse_FadingMeasurement(): Analyse fading measurements and returns the fading rate per decade (g-value). Function version 0.1.16. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., 2021. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.11. https://CRAN.R-project.org/package=Luminescence
Auclair, M., Lamothe, M., Huot, S., 2003. Measurement of anomalous fading for feldspar IRSL using SAR. Radiation Measurements 37, 487-492. doi: 10.1016/S1350-4487(03)00018-0
Huntley, D.J., Lamothe, M., 2001. Ubiquity of anomalous fading in K-feldspars and the measurement
and correction for it in optical dating. Canadian Journal of Earth Sciences 38,
1093-1106. doi: 10.1139/cjes-38-7-1093
Kars, R.H., Wallinga, J., Cohen, K.M., 2008. A new approach towards anomalous fading correction for feldspar IRSL dating-tests on samples in field saturation. Radiation Measurements 43, 786-790. doi: 10.1016/j.radmeas.2008.01.021
Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom)
Christoph Burow, University of Cologne (Germany)
, RLum Developer Team
## load example data (sample UNIL/NB123, see ?ExampleData.Fading) data("ExampleData.Fading", envir = environment()) ##(1) get fading measurement data (here a three column data.frame) fading_data <- ExampleData.Fading$fading.data$IR50 ##(2) run analysis g_value <- analyse_FadingMeasurement( fading_data, plot = TRUE, verbose = TRUE, n.MC = 10)#> #> [analyse_FadingMeasurement()] #> #> n.MC: 10 #> tc: 3.78e+02 s #> --------------------------------------------------- #> T_0.5 interpolated: NA #> T_0.5 predicted: 4e+11 #> g-value: 5.18 ± 0.34 (%/decade) #> g-value (norm. 2 days): 6.01 ± 0.34 (%/decade) #> --------------------------------------------------- #> rho': 3.93e-06 ± 3.81e-07 #> log10(rho'): -5.41 ± 0.04 #> ---------------------------------------------------##(3) this can be further used in the function ## to correct the age according to Huntley & Lamothe, 2001 results <- calc_FadingCorr( age.faded = c(100,2), g_value = g_value, n.MC = 10)#> #> #> [calc_FadingCorr()] #> #> >> Fading correction according to Huntley & Lamothe (2001) #> #> .. used g-value: 5.182 ± 0.337 %/decade #> .. used tc: 1.198e-08 ka #> .. used kappa: 0.0225 ± 0.0015 #> ---------------------------------------------- #> seed: NA #> n.MC: 10 #> observations: 10 #> ---------------------------------------------- #> Age (faded): 100 ka ± 2 ka #> Age (corr.): 203.0811 ka ± 13.4105 ka #> ----------------------------------------------