Description Author Notes Vignettes Bilateral index functions Similarity chain linking Multilateral index functions Other index number functions Data preparation functions Data exploration functions Sample data Differences approach to index numbers Time index functions
IndexNumR is a package for computing bilateral and multilateral index numbers. The package has been designed with performance in mind, to enable computing index numbers on large datasets within a reasonable timeframe. It also aims to make a large number of index number methods available, along with access to datasets to enable research and experimentation.
I'd like to thank all those that have commented on, or tested the code so that it could be improved. In particular, I'd like to thank Professor Kevin Fox at the University of New South Wales for his support and input.
Some function parameters can have a considerable impact on the outputs, so it is recommended that the user read the documentation for these functions carefully.
There is very detailed information about the functions in the package vignette, which can be accessed with,
Compute bilateral indexes
Compute dissimilarity measures or chain links.
Compute multilateral indexes
Perform various operations on the data before using other functions, such as index number functions.
Learn more about the characteristics of your dataset.
IndexNumR has one sample dataset,
and a function for generating small datasets,
and a function for accessing the Dominicks Finer Foods scanner data,
These functions are referred to as indicators, to distinguish them from the bilateral and multilateral index functions which use the ratio approach.
Index functions in IndexNumR generally need a time period variable. These functions will compute the required time period variable, depending on the frequency required.
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