piar 0.9.0

Significant changes

• The internal representation of index objects has changed so that both
  the index and contrib components of an index are now matrices instead of
  lists. This simplifies the code base and in some cases improves performance, but
  will break any code that directly uses the internal components of an index.

• A new internal optimization means that index objects without contributions now
  consume about half as much memory.

• contrib() and contrib2DF() are no longer generic functions. (They were
  originally generic to allow for the possibility of an index subclass without
  contributions, but that is no longer required.)

• In most cases methods have optional arguments after the .... This means that
  in some cases arguments need to be named that previously could be passes by position.

  • link and base in chain(), unchain(), and rebase().
  • period in update().

• The default behavior for aggregating duplicate contributions is to sum them.
  This means that it is now possible to have duplicate products across levels
  in elementary_index().

• The margin argument in split(index) has been renamed to along.

Improvements

• Added a new function combine_classifications() to more easily build an
  aggregation structure that spans multiple hierarchical classifications.

• Subscripting an index object with a matrix is now more flexible and can
  return/replace a list of index objects.

• Added a new function impute_prices() to consolidate the different
  price-imputation functions.

Bug fixes

• Setting contrib = FALSE in aggregate(index) always returns an index with
  no contributions.

• set_weights() no longer returns its result invisibly.

• update(pias, index) now correctly coerces index to a fixed-base index when
  it is not an index object, as documented.

Deprecations

• carry_forward(), carry_backward(), and shadow_price() are deprecated.
  Use impute_prices() instead.

piar 0.8.3

Improvements

• Both aggregate(index) and mean(index) get a new argument duplicate_contrib
  to control how product contributions are made when there are duplicate products.

• Coercing an index or an aggregation structure to a matrix now has dimension
  names. Same with the output from contrib().

• expand_classification() and split_classification() get a new argument
  pad to better manage unbalanced classifications.

• It is no longer possible to make non-positive index values or use
  negative weights.

Bug fixes

• Fixed description of how product contributions are combined across subperiods
  in ?mean.piar_index (#51).

• Converting a data frame with partial product contributions to an index object
  no longer gives an error (#52).

• It is now an error to construct product contributions for a superlative index
  when missing/zero weights are mismatched (#59).

piar 0.8.2

• The vignette has been re-written, split into small examples that cover more
  topics, and should be easier to follow.

Improvements

• Added set_levels(), set_time(), and set_weights() to make it easier to
  replace levels, times, and weights with pipes.

• contrib(index) <- value can now be used to replace product contributions. The
  alias set_contrib() is easier to use with pipes.

• elementary_index() is now an alias for elemental_index() as this is
  more common in the literature.

• aggregate() can now use two aggregation structures to make a superlative
  index.

• cut(aggregation_structure) can be used cut off the bottom/top of an
  aggregation structure. Works in conjunction with set_contrib_from_index() to
  calculate index-level contributions.

• Aggregation structures now preserve the names of their levels to work
  with cut(). This means that as.data.frame(aggregation_structure) can produce
  different column names.

• as.data.frame(index) gets an option to make a list-column of percent-change
  contributions. as_index(data.frame) gets an analogous option to add
  contributions in a table to an index.

• as.ts(index) can now be used to turn an index into a regular time series and
  as_index(ts) can turn a time series into an index object.

• split_classification() gives another way to generate an aggregation structure
  from a character vector.

Bug fixes

• as.data.frame() methods now respect the signature of the generic. This
  allows row names to be set and prevents superfluous warnings when trying to
  use data.frame(); e.g., with write.csv() (#34).

• Subscripting an index object with a length 0 vector is no longer an error (#48).

piar 0.8.1

Significant changes

• elemental_index(), price_relative(), shadow_price(), carry_forward(),
  and carry_backward() now have a formula interface to select the relevant,
  e.g., price variables from a data frame instead of using with(). This
  changes the signature of these functions, and may break old code if argument
  were not named.

  • as_aggregation_structure(list) and mean(index) now require the weights
    argument to be named to be consistent with other functions.

• The aggregate_piar_index class has been removed. This class was not
  well thought out, and added unnecessary restrictions and complications to
  certain functions. In most cases this has little impact on existing code, but
  does mean that the few functions related to aggregate indexes have been removed.

• The deprecated cols argument for as_index(data.frame) has been removed.

• The default window size for mean(index) now covers the entire index. This
  makes it so that mean() doesn't assume an index is monthly, and
  makes it easier to use mean() with the new window() method for index
  object.

Improvements

• as_index() gains a new argument contrib to add contributions to
  pre-computed indexes.

• Added contrib2DF() to extract percent-change contributions as a data frame.

• elemental_index(), price_relative(), shadow_price(), carry_forward(),
  and carry_backward() now require the arguments for time periods, products, and
  elemental aggregates to be named so as to avoid accidentally changing the order
  of these arguments (gh #7).

• Added interact_classifications() to get the interaction of different
  dimensions for a hierarchical classification.

• unchain() gets an new argument base for better interaction with
  chain() and rebase().

• aggregate(index) gets a new argument include_ea to control whether
  elemental indexes are returned when aggregating.

• The summary() method for indexes has been changed to simply print a
  summary of the index, rather than try to summarized the index values.

• aggregate(index) now imputes percent-change contributions for missing index
  values when na.rm = TRUE. The previously undocumented behavior was to simply
  drop them.

• Added window(index) to extract a window of price indexes and
  window(index) <- value to replace them.

• The base period for rebase() can now be a time period specifying a new base
  period. This makes it easier to rebase with pipes; e.g.,
  index |> mean() |> rebase("202001").

• elemental_index() gets a new argument product to better control product
  names.

piar 0.7.0

Significant changes

• Some arguments for elemental_index(), as_index(), aggregate(index), mean(index), vcov(index), update(aggregation_structure), and weights(aggregation_structure) now need to be named (e.g., na.rm, contrib). This helps to unify the signatures for several functions that had similar arguments in different positions. In all cases these are arguments that are not near the beginning of the function and should have probably been named anyways.

• There are several bug fixes in this version that make non-backwards compatible changes.

Improvements

• Added examples for finding imputed index values to the vignette.

• contrib() gets a new argument period to control which time periods get included in the contributions matrix (as documented).

• contrib() gets a new argument pad to control how the contributions matrix is padded when products differ over time.

• Added is.na() and anyNA() methods to find missing values in an index object.

• index[i] <- value now works when i is a matrix.

• mean() gets a new argument contrib to control if product contributions are aggregated over subperiods.

• Added a split() method for index objects.

• levels(aggregation_structure) now returns a list of levels to denote the position of each level in the hierarchy. Use unlist() to get the old behavior.

Bug fixes

• The default for ea_only has changed to TRUE when calling weights(aggregation_structure) to fix a bug with the replacement method.

• Replacing an index value with index[] <- value when value is also an index object now works correctly when value is recycled.

• Setting stringsAsFactors = TRUE in as.data.frame(index) now keeps the correct ordering of the factor levels.

• mean(index) no longer returns an aggregate index when r differs from that used to make index.

Deprecations

• The cols argument for as_index() is deprecated and will be removed in a future version.

piar 0.6.0

Significant changes

• The [[ method for index objects has been removed as it created unexpected problems for little gain. as.matrix(index)[[1, 1]] is a more explicit and flexible way to get the same behavior as index[[1, 1]].

• aggregation_structure() now orders the levels of an aggregation according to the order they appear in the data. Previously the levels were ordered lexicographically, except for the elemental aggregates. This can affect the order in which index values appear for an aggregate index.

There are a number of changes to the way product names are handled when making an index and extracting percent-change contributions.

• Names for price relatives now need to be unique within a time period for elemental_index(). The previous (undocumented) behavior was to only require that names be unique within a time period and elemental aggregate. This implies two non-backward compatible changes.

  • The default product names for elemental_index() now include the name of the elemental aggregate to conform to the above requirement.

  • Percent-change contributions from contrib() have simplified row names, as there is now no need to include index-level names to make product names unique.

• contrib() now always returns a matrix. Previously it would return NULL if there were no contributions for each level of the index.

• Rows for the contributions matrix are ordered according to product names so that they have a consistent ordering.

Improvements

• Printing an index gives a textual description in addition to the matrix of index values. Printing an aggregation structure now gives a description and tabular representation instead of a list.

• There are now methods to set the levels and time periods of an index.

• Methods for index objects are now faster for larger indexes.

• aggregate() gains a new argument contrib that controls if percent-change contributions for elemental indexes are aggregated. The default maintains the current behavior of aggregating contributions if there are any.

• The class names for index objects have changed to fix a name conflict with Matrix. This means it's now possible to use rsmatrix with piar.

• The as.matrix() method for aggregation structures gains a new argument sparse. If sparse = TRUE then the aggregation matrix is a sparse, rather than dense, matrix. This option can also be used in the vcov() method for aggregate price indexes to improve performance for large indexes.

• Added the carry_backwards() function to do carry backwards (as opposed to carry forwards) imputation.

Bug fixes

• Viewing index objects in the RStudio viewer longer gives an error.

• is_direct_index() is now exported.

• Replacing index values for an aggregate index no longer returns an aggregate index, as it may not be consistent in aggregation.

• Stacking two indexes now only returns an aggregate index if both indexes are themselves aggregate indexes. Previously it was possible to stack an aggregate index with a non-aggregate index to produce an aggregate index that was not consistent in aggregation.

piar 0.5.0

Significant changes

• piar now requires R >= 4.0.

• is_chain_index() has been removed; use is_chainable_index() instead.

• The first argument to elemental_index() is now x, not rel, to be consistent with the rest of the functions. Similarly, the first argument for expand_classification() is now x, not class.

New features

• New functions as_aggregation_structure() and is_aggregation_structure() to coerce (usually) tabular data for aggregation weights into an aggregation structure, and test if an object is an aggregation structure.

• A method for [[ for index objects to extract or replace a single index value.

• The weights for an aggregation structure can be replace with weights(pias) <- vector.

Improvements

• The levels() replacement function now gives an error for indexes and aggregation structures, rather than adding a levels attribute that does nothing.

• The width argument for expand_classification() now recycles a single value.

• Major overhaul of the documentation should make it easier to use.

• The object structure used to represent index object has been refined.

• Subscripting an index object is now much faster.

• It is now possible to update an aggregation structure with a non-aggregated index.

• Functions that accept a price index or an aggregation structure as an argument now attempt to coerce these arguments into an index object or aggregation structure object instead of throwing an error.

Bug fixes

• Fixed a bug where creating elemental indexes with missing product names could produce a contributions matrix with the wrong number of products.

• It is now possible to chain an index with only one level.

• Subscripting an index with NAs or duplicate indices is no longer allowed.