Extract percent-change contributions

Extract a matrix of percent-change contributions from a price index.

Usage

contrib(x, ...)

# S3 method for piar_index
contrib(x, level = levels(x)[1L], period = time(x), ..., pad = 0)

Arguments

x

A price index, as made by, e.g., elemental_index().

...

Further arguments passed to or used by methods.

level

The level of an index for which percent-change contributions are desired, defaulting to the first level (usually the top-level for an aggregate index).

period

The time periods for which percent-change contributions are desired, defaulting to all time periods.

pad

A numeric value to pad contributions so that they fit into a rectangular array when products differ over time. The default is 0.

Value

A matrix of percent-change contributions with a column for each period and a row for each product (sorted) for which there are contributions in level. Contributions are padded with pad to fit into a rectangular array when products differ over time.

See also

Other index methods: [.piar_index(), aggregate.piar_index(), as.data.frame.piar_index(), chain(), head.piar_index(), is.na.piar_index(), levels.piar_index(), mean.piar_index(), merge.piar_index(), split.piar_index(), stack.piar_index(), time.piar_index(), window.piar_index()

Examples

prices <- data.frame(
  rel = 1:8,
  period = rep(1:2, each = 4),
  ea = rep(letters[1:2], 4)
)

index <- with(
  prices,
  elemental_index(rel, period, ea, contrib = TRUE)
)

pias <- aggregation_structure(
  list(c("top", "top", "top"), c("a", "b", "c")), 1:3
)

index <- aggregate(index, pias, na.rm = TRUE)

# Percent-change contributions for the top-level index

contrib(index)
#>             1         2
#> a.1 0.0000000 0.5081686
#> a.2 0.2440169 0.6442213
#> b.1 0.3905243 2.0513858
#> b.2 0.8284271 2.4871732

# Calculate EA contributions for the chained index

library(gpindex)

arithmetic_contributions(
  as.matrix(chain(index))[c("a", "b", "c"), 2],
  weights(pias)
)
#>        a        b        c 
#> 1.541158 6.198639 7.739798