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Modelling incomplete and heterogeneous bleaching of mobile grains partially exposed to the light, an implementation of the EED model proposed by Guibert et al. (2019).
calc_EED_Model(
data,
D0 = 120L,
expected_dose,
MinIndivDose = NULL,
MaxIndivDose = NULL,
kappa = NULL,
sigma_distr = NULL,
n.simul = 5000L,
n.minSimExp = 50L,
sample_name = "",
method_control = list(),
verbose = TRUE,
plot = TRUE,
...
)data.frame (required): input data consisting of two columns, the De and the SE(De). Values are expected in Gy
integer (with default): D0 value (in Gy), defining the characterisation behaviour of the quartz.
numeric (required): expected equivalent dose
numeric (with default): value specifying the minimum dose taken into
account for the plateau. NULL applies all values.
numeric (with default): value specifying the maximum dose taken into
account for the plateau. NULL applies all values.
numeric (optional): positive dimensionless exposure parameter characterising the bleaching state of the grains. Low values (< 10) indicate poor bleaching
numeric (optional): positive dose rate parameter, representing the dose variability to which the grains were exposed ##TODO perhaps it should be renamed
integer (with default): number of simulations
integer (with default): number of MC runs for calculating the uncertainty contribution from the sampling
character (with default): name of the sample
list (with default): additional deep control parameters, parameters need to be provided as named list, see details
logical (with default): enable/disable output to the terminal.
logical (with default): enable/disable the plot output.
further parameters that can be passed to better control the plot output. Support arguments
are xlab, xlim.
0.1.0
Guibert, P., Kreutzer, S., 2025. calc_EED_Model(): Modelling Exponential Exposure Distribution. Function version 0.1.0. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J., Mercier, N., Philippe, A., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., Galharret, J., Colombo, M., Steinbuch, L., Boer, A.d., 2025. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 1.0.1. https://r-lum.github.io/Luminescence/
Pierre Guibert, IRAMAT-CRP2A, UMR 5060, Université Bordeaux Montaigne (France), Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom) , RLum Developer Team
The function is an implementation and enhancement of the scripts used in
Guibert et al. (2019). The implementation supports a semi-automated estimation
of the parameters kappa and sigma_distr. If set to NULL, a surface interpolation
is used to estimated those values.
Method control parameters
| ARGUMENT | FUNCTION | DEFAULT | DESCRIPTION |
lower | - | c(0.1,0,0) | set lower bounds for kappa, sigma, and the expected De in auto mode |
upper | - | c(1000,2) | set upper bounds for kappa, sigma, and the expected De in auto mode |
iter_max | - | 1000 | maximum number for iterations for used to find kappa and sigma |
trace | - | FALSE | enable/disable terminal trace mode; overwritten by global argument verbose |
trace_plot | - | FALSE | enable/disable additional trace plot output; overwritten by global argument verbose |
Guibert, P., Christophe, C., Urbanova, P., Guérin, G., Blain, S., 2017. Modelling incomplete and heterogeneous bleaching of mobile grains partially exposed to the light - Towards a new tool for single grain OSL dating of poorly bleached mortars. Radiation Measurements 107, 48–57. tools:::Rd_expr_doi("10.1016/j.radmeas.2017.10.003")
RLum.Results, calc_MinDose, calc_FuchsLang2001, calc_IEU, calc_FiniteMixture
data(ExampleData.MortarData, envir = environment())
calc_EED_Model(
data = MortarData,
kappa = 14,
sigma_distr = 0.37,
expected_dose = 11.7)
## automated estimation of
## sigma_distribution and
## kappa
if (FALSE) {
calc_EED_Model(
data = MortarData,
kappa = NULL,
sigma_distr = NULL,
expected_dose = 11.7)
}
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