Extended variant of HierarchyCompute with several column variables (not just "colFactor").
Parameter colVar splits the hierarchy variables in two groups and this variable overrides the difference between "rowFactor" and "colFactor".
Usage
HierarchyCompute2(
data,
hierarchies,
valueVar,
colVar,
rowSelect = NULL,
colSelect = NULL,
select = NULL,
output = "data.frame",
...
)Arguments
- data
The input data frame
- hierarchies
A named list with hierarchies
- valueVar
Name of the variable(s) to be aggregated
- colVar
Name of the column variable(s)
- rowSelect
Data frame specifying variable combinations for output
- colSelect
Data frame specifying variable combinations for output
- select
Data frame specifying variable combinations for output
- output
One of "data.frame" (default), "outputMatrix", "matrixComponents".
- ...
Further parameters sent to
HierarchyCompute
Details
Within this function, HierarchyCompute is called two times.
By specifying output as "matrixComponents",
output from the two runs are retuned as a list with elements hcRow and hcCol.
The matrix multiplication in HierarchyCompute is extended to
outputMatrix = hcRow$dataDummyHierarchy
%*% hcRow$valueMatrix
%*% t(hcCol$dataDummyHierarchy).
This is modified in cases with more than a single valueVar.
Note
There is no need to call HierarchyCompute2 directly.
The main function HierarchyCompute can be used instead.
Examples
x <- SSBtoolsData("sprt_emp")
geoHier <- SSBtoolsData("sprt_emp_geoHier")
ageHier <- SSBtoolsData("sprt_emp_ageHier")
HierarchyCompute(x, list(age = ageHier, geo = geoHier, year = "rowFactor"), "ths_per",
colVar = c("age", "year"))
#> age year geo ths_per
#> 1 Y15-64 2014 Europe 222.3
#> 2 Y15-64 2014 nonEU 3.3
#> 3 Y15-64 2014 EU 219.0
#> 4 Y15-64 2015 Europe 225.0
#> 5 Y15-64 2015 nonEU 3.5
#> 6 Y15-64 2015 EU 221.5
#> 7 Y15-64 2016 Europe 233.5
#> 8 Y15-64 2016 nonEU 3.8
#> 9 Y15-64 2016 EU 229.7
HierarchyCompute(x, list(age = ageHier, geo = geoHier, year = "rowFactor"), "ths_per",
colVar = c("age", "geo"))
#> age geo year ths_per
#> 1 Y15-64 Europe 2014 222.3
#> 2 Y15-64 Europe 2015 225.0
#> 3 Y15-64 Europe 2016 233.5
#> 4 Y15-64 nonEU 2014 3.3
#> 5 Y15-64 nonEU 2015 3.5
#> 6 Y15-64 nonEU 2016 3.8
#> 7 Y15-64 EU 2014 219.0
#> 8 Y15-64 EU 2015 221.5
#> 9 Y15-64 EU 2016 229.7
HierarchyCompute(x, list(age = ageHier, geo = geoHier, year = "rowFactor"), "ths_per",
colVar = c("age", "year"), output = "matrixComponents")
#> $hcRow
#> $hcRow$dataDummyHierarchy
#> 3 x 3 sparse Matrix of class "dgCMatrix"
#>
#> Europe 1 1 1
#> nonEU 1 . .
#> EU 0 1 1
#>
#> $hcRow$valueMatrix
#> 3 x 6 sparse Matrix of class "dgCMatrix"
#> 1 2 3 4 5 6
#> [1,] 1.8 1.9 1.9 1.5 1.6 1.9
#> [2,] 11.6 14.2 12.7 20.2 24.3 25.8
#> [3,] 66.9 63.4 69.1 120.3 119.6 122.1
#>
#> $hcRow$fromCrossCode
#> geo
#> 1 Iceland
#> 2 Portugal
#> 3 Spain
#>
#> $hcRow$toCrossCode
#> geo
#> 1 Europe
#> 2 nonEU
#> 3 EU
#>
#>
#> $hcCol
#> $hcCol$dataDummyHierarchy
#> 3 x 6 sparse Matrix of class "dgCMatrix"
#>
#> Y15-64:2014 1 . . 1 . .
#> Y15-64:2015 . 1 . . 1 .
#> Y15-64:2016 . . 1 . . 1
#>
#> $hcCol$codeFrame
#> age year
#> 1 Y15-64 2014
#> 2 Y15-64 2015
#> 3 Y15-64 2016
#>
#>
HierarchyCompute(x, list(age = ageHier, geo = geoHier, year = "rowFactor"), "ths_per",
colVar = c("age", "geo"), output = "matrixComponents")
#> $hcRow
#> $hcRow$dataDummyHierarchy
#> 3 x 3 sparse Matrix of class "dgCMatrix"
#>
#> 2014 1 . .
#> 2015 . 1 .
#> 2016 . . 1
#>
#> $hcRow$valueMatrix
#> 3 x 6 sparse Matrix of class "dgCMatrix"
#> 1 2 3 4 5 6
#> [1,] 1.8 11.6 66.9 1.5 20.2 120.3
#> [2,] 1.9 14.2 63.4 1.6 24.3 119.6
#> [3,] 1.9 12.7 69.1 1.9 25.8 122.1
#>
#> $hcRow$fromCrossCode
#> year
#> 1 2014
#> 2 2015
#> 3 2016
#>
#> $hcRow$toCrossCode
#> year
#> 1 2014
#> 2 2015
#> 3 2016
#>
#>
#> $hcCol
#> $hcCol$dataDummyHierarchy
#> 3 x 6 sparse Matrix of class "dgCMatrix"
#>
#> Y15-64:Europe 1 1 1 1 1 1
#> Y15-64:nonEU 1 . . 1 . .
#> Y15-64:EU 0 1 1 0 1 1
#>
#> $hcCol$codeFrame
#> age geo
#> 1 Y15-64 Europe
#> 2 Y15-64 nonEU
#> 3 Y15-64 EU
#>
#>