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Calculate Lx/Tx ratio for CW-OSL curves

Source: R/calc_OSLLxTxRatio.R
calc_OSLLxTxRatio.Rd

Calculate Lx/Tx ratios from a given set of CW-OSL curves assuming late light background subtraction.

Usage

calc_OSLLxTxRatio(
  Lx.data,
  Tx.data = NULL,
  signal.integral,
  signal.integral.Tx = NULL,
  background.integral,
  background.integral.Tx = NULL,
  background.count.distribution = "non-poisson",
  use_previousBG = FALSE,
  sigmab = NULL,
  sig0 = 0,
  digits = NULL
)

Arguments

Lx.data

RLum.Data.Curve or data.frame (required): requires a CW-OSL shine down curve (x = time, y = counts)

Tx.data

RLum.Data.Curve or data.frame (optional): requires a CW-OSL shine down curve (x = time, y = counts). If no input is given the Tx.data will be treated as NA and no Lx/Tx ratio is calculated.

signal.integral

numeric (required): vector with the limits for the signal integral. Can be set to NA than now integrals are considered and all other integrals are set to NA as well.

signal.integral.Tx

numeric (optional): vector with the limits for the signal integral for the Tx-curve. If nothing is provided the value from signal.integral is used.

background.integral

numeric (required): vector with the bounds for the background integral. Can be set to NA than now integrals are considered and all other integrals are set to NA as well.

background.integral.Tx

numeric (optional): vector with the limits for the background integral for the Tx curve. If nothing is provided the value from background.integral is used.

background.count.distribution

character (with default): sets the count distribution assumed for the error calculation. Possible arguments poisson or non-poisson. See details for further information

use_previousBG

logical (with default): If set to TRUE the background of the Lx-signal is subtracted also from the Tx-signal. Please note that in this case separate signal integral limits for the Tx-signal are not allowed and will be reset.

sigmab

numeric (optional): option to set a manual value for the overdispersion (for LnTx and TnTx), used for the Lx/Tx error calculation. The value should be provided as absolute squared count values, e.g. sigmab = c(300,300). Note: If only one value is provided this value is taken for both (LnTx and TnTx) signals.

sig0

numeric (with default): allow adding an extra component of error to the final Lx/Tx error value (e.g., instrumental error, see details).

digits

integer (with default): round numbers to the specified digits. If digits is set to NULL nothing is rounded.

Value

Returns an S4 object of type RLum.Results.

Slot data contains a list with the following structure:

@data

$LxTx.table (data.frame)
.. $ LnLx
.. $ LnLx.BG
.. $ TnTx
.. $ TnTx.BG
.. $ Net_LnLx
.. $ Net_LnLx.Error
.. $ Net_TnTx
.. $ Net_TnTx.Error
.. $ LxTx
.. $ LxTx.Error
$ calc.parameters (list)
.. $ sigmab.LnTx
.. $ sigmab.TnTx
.. $ k

@info

$ call (original function call)

Details

The integrity of the chosen values for the signal and background integral is checked by the function; the signal integral limits have to be lower than the background integral limits. If a vector is given as input instead of a data.frame, an artificial data.frame is produced. The error calculation is done according to Galbraith (2002).

Please note: In cases where the calculation results in NaN values (for example due to zero-signal, and therefore a division of 0 by 0), these NaN values are replaced by 0.

sigmab

The default value of sigmab is calculated assuming the background is constant and would not applicable when the background varies as, e.g., as observed for the early light subtraction method.

sig0

This argument allows to add an extra component of error to the final Lx/Tx error value. The input will be treated as factor that is multiplied with the already calculated LxTx and the result is add up by:

$$se(LxTx) = \sqrt(se(LxTx)^2 + (LxTx * sig0)^2)$$

background.count.distribution

This argument allows selecting the distribution assumption that is used for the error calculation. According to Galbraith (2002, 2014) the background counts may be overdispersed (i.e. do not follow a Poisson distribution, which is assumed for the photomultiplier counts). In that case (might be the normal case) it has to be accounted for the overdispersion by estimating \(\sigma^2\) (i.e. the overdispersion value). Therefore the relative standard error is calculated as:

  • poisson $$rse(\mu_{S}) \approx \sqrt(Y_{0} + Y_{1}/k^2)/Y_{0} - Y_{1}/k$$

  • non-poisson $$rse(\mu_{S}) \approx \sqrt(Y_{0} + Y_{1}/k^2 + \sigma^2(1+1/k))/Y_{0} - Y_{1}/k$$

Please note that when using the early background subtraction method in combination with the 'non-poisson' distribution argument, the corresponding Lx/Tx error may considerably increase due to a high sigmab value. Please check whether this is valid for your data set and if necessary consider to provide an own sigmab value using the corresponding argument sigmab.

Note

The results of this function have been cross-checked with the Analyst (version 3.24b). Access to the results object via get_RLum.

Caution: If you are using early light subtraction (EBG), please either provide your own sigmab value or use background.count.distribution = "poisson".

Function version

0.8.0

How to cite

Kreutzer, S., 2024. calc_OSLLxTxRatio(): Calculate Lx/Tx ratio for CW-OSL curves. Function version 0.8.0. 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., 2024. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.26. https://r-lum.github.io/Luminescence/

References

Duller, G., 2018. Analyst v4.57 - User Manual. https://users.aber.ac.uk/ggd

Galbraith, R.F., 2002. A note on the variance of a background-corrected OSL count. Ancient TL, 20 (2), 49-51.

Galbraith, R.F., 2014. A further note on the variance of a background-corrected OSL count. Ancient TL, 31 (2), 1-3.

See also

RLum.Data.Curve, Analyse_SAR.OSLdata, plot_GrowthCurve, analyse_SAR.CWOSL

Author

Sebastian Kreutzer, Institute of Geography, Heidelberg University (Germany) , RLum Developer Team

Examples


##load data
data(ExampleData.LxTxOSLData, envir = environment())

##calculate Lx/Tx ratio
results <- calc_OSLLxTxRatio(
 Lx.data = Lx.data,
 Tx.data = Tx.data,
 signal.integral = c(1:2),
 background.integral = c(85:100))

##get results object
get_RLum(results)
#>    LnLx LnLx.BG TnTx TnTx.BG Net_LnLx Net_LnLx.Error Net_TnTx Net_TnTx.Error
#> 1 81709     530 7403     513    81179       286.5461     6890       88.53581
#>       LxTx LxTx.Error
#> 1 11.78215  0.1570077