predictedShares

You should not need to call this function directly unless the shares
themselves are of interest. Other functions will call this function internally.

Computes bilateral and multilateral index numbers.
It has support for many standard bilateral indexes as well as
multilateral index number methods such as GEKS, GEKS-Tornqvist
(or CCDI), Geary-Khamis and the weighted time product dummy
(for details on these methods see Diewert and Fox (2020)
<doi:10.1080/07350015.2020.1816176>).
It also supports updating of multilateral indexes using
several splicing methods.

Graham White

IndexNumR

Index Number Calculation

predictedShares function

<dl><dt>x</dt>
<dd>A dataframe containing price, quantity, a time period identifier
and a product identifier. It must have column names.</dd>
<dt>pvar</dt>
<dd>A character string for the name of the price variable</dd>
<dt>qvar</dt>
<dd>A character string for the name of the quantity variable. For
elementary indexes a quantity variable is not required for the calculations
and you must specify qvar = "".</dd>
<dt>pervar</dt>
<dd>A character string for the name of the time variable. This variable
must contain integers starting at period 1 and increasing in increments of 1 period.
There may be observations on multiple products for each time period.</dd>
<dt>prodID</dt>
<dd>A character string for the name of the product identifier</dd></dl>

Arguments

Predicted shares for predicted share relative price dissimilarity — predictedShares

<dl>

<dt>x</dt>
<dd>A dataframe containing price, quantity, a time period identifier
and a product identifier. It must have column names.</dd>


<dt>pvar</dt>
<dd>A character string for the name of the price variable</dd>


<dt>qvar</dt>
<dd>A character string for the name of the quantity variable. For
elementary indexes a quantity variable is not required for the calculations
and you must specify qvar = "".</dd>


<dt>pervar</dt>
<dd>A character string for the name of the time variable. This variable
must contain integers starting at period 1 and increasing in increments of 1 period.
There may be observations on multiple products for each time period.</dd>


<dt>prodID</dt>
<dd>A character string for the name of the product identifier</dd>

</dl>

predictedShares: Predicted shares for predicted share relative price dissimilarity

Description

Usage

Value

Arguments