Package index • piar

Calculate price indexes

Functions to make elementary and aggregated price indexes.

elementary_index() elemental_index(): Make elementary/elemental price indexes

as_index(): Coerce to a price index

aggregate(<chainable_piar_index>) aggregate(<direct_piar_index>): Aggregate elementary price indexes

mean(<chainable_piar_index>) mean(<direct_piar_index>): Aggregate a price index over subperiods

Manipulate price indexes

Helpful functions for working with price indexes.

chain() unchain() rebase(): Chain and rebase a price index

merge(<chainable_piar_index>) merge(<direct_piar_index>): Merge price indexes

stack(<chainable_piar_index>) stack(<direct_piar_index>) unstack(<chainable_piar_index>) unstack(<direct_piar_index>): Stack price indexes

`[`(<piar_index>) `[<-`(<piar_index>): Extract and replace index values

window(<piar_index>) `window<-`(<piar_index>): Index window

head(<piar_index>) tail(<piar_index>): Return the first/last parts of an index

contrib() contrib2DF() `contrib<-`() set_contrib() set_contrib_from_index(): Extract percent-change contributions

split(<piar_index>) `split<-`(<piar_index>): Split an index into groups

levels(<piar_index>) `levels<-`(<piar_index>) set_levels(): Get the levels for a price index

time(<piar_index>) `time<-`() set_time() start(<piar_index>) end(<piar_index>) ntime(): Get the time periods for a price index

as.data.frame(<piar_index>) as.matrix(<piar_index>): Coerce an index into a tabular form

as.ts(<piar_index>): Coerce an index into a time series

is.na(<piar_index>) anyNA(<piar_index>): Missing values in a price index

Manipulate prices

Helpful functions for working with prices.

shadow_price() carry_forward() carry_backward(): Impute missing prices

price_relative(): Calculate period-over-period price relatives

Aggregation structure

Functions to make and work with price-index aggregation structures.

aggregation_structure(): Make a price index aggregation structure

expand_classification() interact_classifications(): Expand a hierarchical classification

split_classification(): Split a hierarchical classification

as_aggregation_structure(): Coerce to an aggregation structure

as.matrix(<piar_aggregation_structure>) as.data.frame(<piar_aggregation_structure>): Coerce an aggregation structure into a tabular form

weights(<piar_aggregation_structure>) `weights<-`() set_weights(): Get the weights for an aggregation structure

levels(<piar_aggregation_structure>): Get the levels for an aggregation structure

update(<piar_aggregation_structure>): Update an aggregation structure

cut(<piar_aggregation_structure>): Cut an aggregation structure

is_aggregation_structure(): Test if an object is an aggregation structure

Index objects

The model used to represent price indexes.

piar_index chainable_piar_index direct_piar_index: Price index objects

is_index() is_chainable_index() is_direct_index(): Test if an object is a price index

Sample data

price_data ms_prices ms_weights fs_prices fs_weights: Price data