General merge function for RLum S4 class objects

Function calls object-specific merge functions for RLum S4 class objects.

Usage

merge_RLum(objects, ...)

Arguments

objects: list of RLum (required): list of S4 object of class RLum
...: further arguments that one might want to pass to the specific merge function

Value

Return is the same as input objects as provided in the list.

Details

The function provides a generalised access point for merging specific RLum objects. Depending on the input object, the corresponding merge function will be selected. Allowed arguments can be found in the documentation of each merge function. Empty list elements (NULL) are automatically removed from the input list.

object		corresponding merge function
RLum.Data.Curve	:	`merge_RLum.Data.Curve`
RLum.Analysis	:	`merge_RLum.Analysis`
RLum.Results	:	`merge_RLum.Results`

Note

So far not for every RLum object a merging function exists.

Function version

0.1.3

Author

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

How to cite

Kreutzer, S., 2024. merge_RLum(): General merge function for RLum S4 class objects. Function version 0.1.3. 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/

Examples



##Example based using data and from the calc_CentralDose() function

##load example data
data(ExampleData.DeValues, envir = environment())

##apply the central dose model 1st time
temp1 <- calc_CentralDose(ExampleData.DeValues$CA1)
#> 
#>  [calc_CentralDose]
#> 
#> ----------- meta data ----------------
#>  n:                       62
#>  log:                     TRUE
#> ----------- dose estimate ------------
#>  abs. central dose:       65.71
#>  abs. SE:                 3.05
#>  rel. SE [%]:             4.65
#> ----------- overdispersion -----------
#>  abs. OD:                 22.79
#>  abs. SE:                 2.27
#>  OD [%]:                  34.69
#>  SE [%]:                  3.46
#> -------------------------------------
#> 


##apply the central dose model 2nd time
temp2 <- calc_CentralDose(ExampleData.DeValues$CA1)
#> 
#>  [calc_CentralDose]
#> 
#> ----------- meta data ----------------
#>  n:                       62
#>  log:                     TRUE
#> ----------- dose estimate ------------
#>  abs. central dose:       65.71
#>  abs. SE:                 3.05
#>  rel. SE [%]:             4.65
#> ----------- overdispersion -----------
#>  abs. OD:                 22.79
#>  abs. SE:                 2.27
#>  OD [%]:                  34.69
#>  SE [%]:                  3.46
#> -------------------------------------
#> 

##merge the results and store them in a new object
temp.merged <- get_RLum(merge_RLum(objects = list(temp1, temp2)))