Function returns De value and De value error using the global standardised growth curve (gSGC) assumption proposed by Li et al., 2015 for OSL dating of sedimentary quartz
calc_gSGC(data, gSGC.type = "0-250", gSGC.parameters, n.MC = 100,
verbose = TRUE, plot = TRUE, ...)data.frame (required): input data of providing the following columns: 'LnTn', 'LnTn.error', Lr1Tr1', 'Lr1Tr1.error', 'Dr1' Note: column names are not required. The function expect the input data in the given order
character (with default):
define the function parameters that
should be used for the iteration procedure: Li et al., 2015 (Table 2)
presented function parameters for two dose ranges: "0-450" and "0-250"
list (optional):
option to provide own function parameters used for fitting as named list.
Nomenclature follows Li et al., 2015, i.e. list(A,A.error,D0,D0.error,c,c.error,Y0,Y0.error,range),
range requires a vector for the range the function is considered as valid, e.g. range = c(0,250)
Using this option overwrites the default parameter list of the gSGC, meaning the argument
gSGC.type will be without effect
integer (with default): number of Monte Carlo simulation runs for error estimation, see details.
logical: enable or disable terminal output
logical: enable or disable graphical feedback as plot
parameters will be passed to the plot output
Returns an S4 object of type '>RLum.Results.
@data
$ De.value (data.frame)
.. $ De
.. $ De.error
.. $ Eta
$ De.MC (list) contains the matricies from the error estimation.
$ uniroot (list) contains the uniroot outputs of the De estimations
@info
`$ call`` (call) the original function call
0.1.1 (2018-01-21 17:22:38)
Kreutzer, S. (2018). calc_gSGC(): Calculate De value based on the gSGC by Li et al., 2015. Function version 0.1.1. In: Kreutzer, S., Burow, C., Dietze, M., Fuchs, M.C., Schmidt, C., Fischer, M., Friedrich, J. (2018). Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.8.6. https://CRAN.R-project.org/package=Luminescence
The error of the De value is determined using a Monte Carlo simulation approach.
Solving of the equation is realised using uniroot.
Large values for n.MC will significantly increase the computation time.
Li, B., Roberts, R.G., Jacobs, Z., Li, S.-H., 2015. Potential of establishing a 'global standardised growth curve' (gSGC) for optical dating of quartz from sediments. Quaternary Geochronology 27, 94-104. doi:10.1016/j.quageo.2015.02.011
# NOT RUN {
results <- calc_gSGC(data = data.frame(
LnTn = 2.361, LnTn.error = 0.087,
Lr1Tr1 = 2.744, Lr1Tr1.error = 0.091,
Dr1 = 34.4))
get_RLum(results, data.object = "De")
# }
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