Hierarchies2ModelMatrix: Model matrix representing crossed hierarchies

Description

Make a model matrix, x, that corresponds to data and represents all hierarchies crossed. This means that aggregates corresponding to numerical variables can be computed as t(x) %*% y, where y is a matrix with one column for each numerical variable.

Usage

Hierarchies2ModelMatrix(
  data,
  hierarchies,
  inputInOutput = TRUE,
  crossTable = FALSE,
  total = "Total",
  hierarchyVarNames = c(mapsFrom = "mapsFrom", mapsTo = "mapsTo", sign = "sign", level
    = "level"),
  unionComplement = FALSE,
  reOrder = TRUE,
  select = NULL,
  removeEmpty = FALSE,
  selectionByMultiplicationLimit = 10^7,
  makeColnames = TRUE,
  verbose = FALSE
)

Arguments

data

Matrix or data frame with data containing codes of relevant variables

hierarchies

List of hierarchies, which can be converted by AutoHierarchies. Thus, the variables can also be coded by "rowFactor" or "", which correspond to using the categories in the data.

inputInOutput

Logical vector (possibly recycled) for each element of hierarchies. TRUE means that codes from input are included in output. Values corresponding to "rowFactor" or "" are ignored.

crossTable

Cross table in output when TRUE

total

Vector of total codes (possibly recycled) used when running Hrc2DimList

hierarchyVarNames

Variable names in the hierarchy tables as in HierarchyFix

unionComplement

Logical vector (possibly recycled) for each element of hierarchies. When TRUE, sign means union and complement instead of addition or subtraction. Values corresponding to "rowFactor" and "colFactor" are ignored.

reOrder

When TRUE (default) output codes are ordered in a way similar to a usual model matrix ordering.

select

Data frame specifying variable combinations for output.

removeEmpty

When TRUE and when select=NULL, empty columns (only zeros) are not included in output.

selectionByMultiplicationLimit

With non-NULL select and when the number of elements in the model matrix exceeds this limit, the computation is performed by a slower but more memory efficient algorithm.

makeColnames

Colnames included when TRUE (default).

verbose

Whether to print information during calculations. FALSE is default.

Value

A sparse model matrix or a list of two elements (model matrix and cross table)

Details

This function makes use of AutoHierarchies and HierarchyCompute via HierarchyComputeDummy. Since the dummy matrix is transposed in comparison to HierarchyCompute, the parameter rowSelect is renamed to select and makeRownames is renamed to makeColnames.

Examples

Run this code

# NOT RUN {
# Create some input
z <- SSBtoolsData("sprt_emp_withEU")
ageHier <- SSBtoolsData("sprt_emp_ageHier")
geoDimList <- FindDimLists(z[, c("geo", "eu")], total = "Europe")[[1]]


# First example has list output
Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList), inputInOutput = FALSE, 
                        crossTable = TRUE)


m1 <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList), inputInOutput = FALSE)
m2 <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList))
m3 <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList, year = ""),
                              inputInOutput = FALSE)
m4 <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList, year = "allYears"), 
                              inputInOutput = c(FALSE, FALSE, TRUE))

# Illustrate the effect of unionComplement, geoHier2 as in the examples of HierarchyCompute
geoHier2 <- rbind(data.frame(mapsFrom = c("EU", "Spain"), mapsTo = "EUandSpain", sign = 1), 
                  SSBtoolsData("sprt_emp_geoHier")[, -4])
m5 <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoHier2, year = "allYears"), 
                              inputInOutput = FALSE)  # Spain is counted twice
m6 <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoHier2, year = "allYears"), 
                              inputInOutput = FALSE, unionComplement = TRUE)


# Compute aggregates
ths_per <- as.matrix(z[, "ths_per", drop = FALSE])  # matrix with the values to be aggregated
t(m1) %*% ths_per  # crossprod(m1, ths_per) is equivalent and faster
t(m2) %*% ths_per
t(m3) %*% ths_per
t(m4) %*% ths_per
t(m5) %*% ths_per
t(m6) %*% ths_per


# Example using the select parameter
select <- data.frame(age = c("Y15-64", "Y15-29", "Y30-64"), geo = c("EU", "nonEU", "Spain"))
m2a <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList), select = select)

# Same result by slower alternative
m2B <- Hierarchies2ModelMatrix(z, list(age = ageHier, geo = geoDimList), crossTable = TRUE)
m2b <- m2B$modelMatrix[, Match(select, m2B$crossTable), drop = FALSE]
t(m2b) %*% ths_per
# }