tune_Data function

Tune data for experimental purpose

The error can be reduced and sample size increased for specific purpose.

tune_Data(data, decrease.error = 0, increase.data = 0)

Arguments

• data: data.frame (required ): input values, structure: data (values[,1]) and data error (values [,2]) are required
• decrease.error: numeric : factor by which the error is decreased, ranges between 0 and 1.
• increase.data: numeric : factor by which the error is decreased, ranges between 0 and Inf.

Returns

Returns a data.frame with tuned values.

Note

You should not use this function to improve your poor data set!

Function version

0.5.0

Examples

## load example data set
data(ExampleData.DeValues, envir = environment())
x <- ExampleData.DeValues$CA1

## plot original data
plot_AbanicoPlot(data = x,
                 summary = c("n", "mean"))

## decrease error by 10 %
plot_AbanicoPlot(data = tune_Data(x, decrease.error = 0.1),
                 summary = c("n", "mean"))

## increase sample size by 200 %
#plot_AbanicoPlot(data = tune_Data(x, increase.data = 2) ,
#                summary = c("n", "mean"))

Author(s)

Michael Dietze, GFZ Potsdam (Germany) , RLum Developer Team

How to cite

Dietze, M., 2025. tune_Data(): Tune data for experimental purpose. Function version 0.5.0. 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/