FoReco (version 1.0.0)

df2aggmat: Cross-sectional aggregation matrix of a dataframe

Description

This function allows the user to easily build the (\(n_a \times n_b\)) cross-sectional aggregation matrix starting from a data frame.

Usage

df2aggmat(formula, data, sep = "_", sparse = TRUE, top_label = "Total",
          verbose = TRUE)

Value

A (na x nb) matrix.

Arguments

formula

Specification of the hierarchical structure: grouped hierarchies are specified using ~ g1 * g2 and nested hierarchies are specified using ~ parent / child. Mixtures of the two formulations are also possible, like ~ g1 * (grandparent / parent / child).

data

A dataset in which each column contains the values of the variables in the formula and each row identifies a bottom level time series.

sep

Character to separate the names of the aggregated series, (default is "_").

sparse

Option to return sparse matrices (default is TRUE).

top_label

Label of the top level variable (default is "Total").

verbose

If TRUE (default), hierarchy informations are printed.

See Also

Utilities: FoReco2matrix(), aggts(), balance_hierarchy(), commat(), csprojmat(), cstools(), ctprojmat(), cttools(), lcmat(), recoinfo(), res2matrix(), shrink_estim(), teprojmat(), tetools(), unbalance_hierarchy()

Examples

## Balanced hierarchy
#         T
#    |--------|
#    A        B
#  |---|   |--|--|
# AA   AB  BA BB BC
# Names of the bottom level variables
data_bts <- data.frame(X1 = c("A", "A", "B", "B", "B"),
                       X2 = c("A", "B", "A", "B", "C"),
                       stringsAsFactors = FALSE)
# Cross-sectional aggregation matrix
agg_mat <- df2aggmat(~ X1 / X2, data_bts, sep = "", verbose = FALSE)

## Unbalanced hierarchy
#                 T
#       |---------|---------|
#       A         B         C
#     |---|     |---|     |---|
#    AA   AB   BA   BB   CA   CB
#  |----|         |----|
# AAA  AAB       BBA  BBB
# Names of the bottom level variables
data_bts <- data.frame(X1 = c("A", "A", "A", "B", "B", "B", "C", "C"),
                       X2 = c("A", "A", "B", "A", "B", "B", "A", "B"),
                       X3 = c("A", "B", NA, NA, "A", "B", NA, NA),
                       stringsAsFactors = FALSE)
# Cross-sectional aggregation matrix
agg_mat <- df2aggmat(~ X1 / X2 / X3, data_bts, sep = "", verbose = FALSE)

## Group of two hierarchies
#     T          T         T | A  | B  | C
#  |--|--|  X  |---|  ->  ---+----+----+----
#  A  B  C     M   F       M | AM | BM | CM
#                          F | AF | BF | CF
# Names of the bottom level variables
data_bts <- data.frame(X1 = c("A", "A", "B", "B", "C", "C"),
                       Y1 = c("M", "F", "M", "F", "M", "F"),
                       stringsAsFactors = FALSE)
# Cross-sectional aggregation matrix
agg_mat <- df2aggmat(~ Y1 * X1, data_bts, sep = "", verbose = FALSE)