Function calls object-specific merge functions for RLum S4 class objects.
merge_RLum(objects, ...)
Return is the same as input objects as provided in the list.
The function provides a generalised access point for merge specific
RLum objects. Depending on the input object, the
corresponding merge function will be selected. Allowed arguments can be
found in the documentations 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 |
So far not for every RLum
object a merging function exists.
0.1.3
Kreutzer, S., 2023. 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., 2023. Luminescence: Comprehensive Luminescence Dating Data Analysis. R package version 0.9.23. https://CRAN.R-project.org/package=Luminescence
##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)))