R/calc_TLLxTxRatio.R
calc_TLLxTxRatio.Rd
Calculate Lx/Tx ratio for a given set of TL curves.
calc_TLLxTxRatio( Lx.data.signal, Lx.data.background = NULL, Tx.data.signal, Tx.data.background = NULL, signal.integral.min, signal.integral.max )
Lx.data.signal | RLum.Data.Curve or data.frame (required): TL data (x = temperature, y = counts) (TL signal) |
---|---|
Lx.data.background | RLum.Data.Curve or data.frame (optional): TL data (x = temperature, y = counts). If no data are provided no background subtraction is performed. |
Tx.data.signal | RLum.Data.Curve or data.frame (required): TL data (x = temperature, y = counts) (TL test signal) |
Tx.data.background | RLum.Data.Curve or data.frame (optional): TL data (x = temperature, y = counts). If no data are provided no background subtraction is performed. |
signal.integral.min | integer (required):
channel number for the lower signal integral bound
(e.g. |
signal.integral.max | integer (required):
channel number for the upper signal integral bound
(e.g. |
Returns an S4 object of type RLum.Results.
Slot data
contains a list with the following structure:
$ LxTx.table .. $ LnLx .. $ LnLx.BG .. $ TnTx .. $ TnTx.BG .. $ Net_LnLx .. $ Net_LnLx.Error
Uncertainty estimation
The standard errors are calculated using the following generalised equation:
$$SE_{signal} <- abs(Signal_{net} * BG_f /BG_{signal}$$
where \(BG_f\) is a term estimated by calculating the standard deviation of the sum of the \(L_x\) background counts and the sum of the \(T_x\) background counts. However, if both signals are similar the error becomes zero.
This function has still BETA status! Please further note that a similar
background for both curves results in a zero error and is therefore set to NA
.
0.3.3
Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom)
Christoph Schmidt, University of Bayreuth (Germany)
, RLum Developer Team
Kreutzer, S., Schmidt, C., 2021. calc_TLLxTxRatio(): Calculate the Lx/Tx ratio for a given set of TL curves -beta version-. Function version 0.3.3. 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
##load package example data data(ExampleData.BINfileData, envir = environment()) ##convert Risoe.BINfileData into a curve object temp <- Risoe.BINfileData2RLum.Analysis(TL.SAR.Data, pos = 3) Lx.data.signal <- get_RLum(temp, record.id=1) Lx.data.background <- get_RLum(temp, record.id=2) Tx.data.signal <- get_RLum(temp, record.id=3) Tx.data.background <- get_RLum(temp, record.id=4) signal.integral.min <- 210 signal.integral.max <- 230 output <- calc_TLLxTxRatio(Lx.data.signal, Lx.data.background, Tx.data.signal, Tx.data.background, signal.integral.min, signal.integral.max) get_RLum(output)#> LnLx LnLx.BG TnTx TnTx.BG net_LnLx net_LnLx.Error net_TnTx net_TnTx.Error #> 1 257042 4068 82298 2943 252974 49468.92 79355 21449.72 #> LxTx LxTx.Error #> 1 3.187877 1.485073