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
Usage
calc_gSGC(
data,
gSGC.type = "0-250",
gSGC.parameters,
n.MC = 100,
verbose = TRUE,
plot = TRUE,
...
)
Arguments
- data
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 expects the input data in the given order- gSGC.type
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"
- gSGC.parameters
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 argumentgSGC.type
will be without effect- n.MC
integer (with default): number of Monte Carlo simulation runs for error estimation, see details.
- verbose
logical: enable or disable terminal output
- plot
logical: enable or disable graphical feedback as plot
- ...
parameters will be passed to the plot output
Value
Returns an S4 object of type RLum.Results.
@data
$ De.value
(data.frame) .. $ De
.. $ De.error
.. $ Eta
$ De.MC
(list) contains the matrices from the error estimation.$ uniroot
(list) contains the uniroot outputs of the De estimations
@info
`$ call“ (call) the original function call
Details
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.
How to cite
Kreutzer, S., 2024. 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., Mercier, N., Philippe, A., Riedesel, S., Autzen, M., Mittelstrass, D., Gray, H.J., Galharret, J., Colombo, M., 2024. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.26. https://r-lum.github.io/Luminescence/
References
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
Author
Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany) , RLum Developer Team
Examples
results <- calc_gSGC(data = data.frame(
LnTn = 2.361, LnTn.error = 0.087,
Lr1Tr1 = 2.744, Lr1Tr1.error = 0.091,
Dr1 = 34.4))
#>
#> [calc_gSGC()]
#> Corresponding De based on the gSGC
#>
#> Ln/Tn: 2.361 ± 0.087
#> Lr1/Tr1: 2.744 ± 0.091
#> Dr1: 34.4
#> f(D): 0.787 * (1 - exp(-D /73.9)) + c * D + 0.01791
#> n.MC: 100
#> ------------------------------
#> De: 28.43 ± 1.65
#> ------------------------------
get_RLum(results, data.object = "De")
#> DE DE.ERROR ETA
#> 1 28.42881 1.645562 0.1325632