Showing content from https://cran.r-project.org/web/packages/rms/../Matrix/../piar/vignettes/multiple-data-sources.R below:
## ----------------------------------------------------------------------------- library(piar) # Make an aggregation structure. ms_weights[c("level1", "level2")] <- expand_classification(ms_weights$classification) pias <- ms_weights[c("level1", "level2", "business", "weight")] |> as_aggregation_structure() # Make elemental index. elementals <- ms_prices |> transform( relative = price_relative(price, period = period, product = product) ) |> elemental_index(relative ~ period + business, na.rm = TRUE) elementals ## ----------------------------------------------------------------------------- set.seed(12345) scanner_prices <- data.frame( period = rep(c("201904", time(elementals)), each = 200), product = 1:200, price = round(rlnorm(5 * 200) * 10, 1), quantity = round(runif(5 * 200, 100, 1000)) ) head(scanner_prices) ## ----------------------------------------------------------------------------- library(gpindex) geks_elementals <- with( scanner_prices, fisher_geks(price, quantity, period, product, window = 3) ) |> splice_index() |> t() |> as_index(chainable = FALSE) |> set_levels("B5") |> rebase("202001") geks_elementals ## ----------------------------------------------------------------------------- merge(elementals, geks_elementals) |> aggregate(pias, na.rm = TRUE)
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