# relativeDissimilarity: Computes measures of relative dissimilarity between all... In IndexNumR: Index Number Calculation

## Description

A function to compute the relative price dissimilarity between two vectors of prices.

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```relativeDissimilarity( x, pvar, qvar, pervar, prodID, indexMethod = "fisher", similarityMethod = "logquadratic" ) ```

## Arguments

 `x` A dataframe containing price, quantities, a time period index and a product identifier. `pvar` A string identifying the price variable. `qvar` A string identifying the quantity variable. `pervar` A string identifying the time index variable. `prodID` A string identifying the product ID. `indexMethod` A string identifying the index method to use in the calculation. Not relevant for similarityMethod = PLSpread. Supported methods are fisher and tornqvist. Default is Fisher. `similarityMethod` A string specifying the formula for calculating the relative dissimilarity. Valid options are logquadratic, asymplinear, PLSpread and predictedshare. Default is logquadratic.

## Value

A matrix of dissimilarity measures. The first two columns are the possible combinations of bilateral comparisons and the third column is the dissimilarity measure.

## References

Diewert, W.E. (2002). "Similarity and Dissimilarity Indexes: An Axiomatic Approach" Discussion Paper No. 0210, Department of Economics, University of British Columbia.

## Examples

 ```1 2 3 4 5``` ```# estimate the dissimilarity between periods in the CES_sigma_2 dataset # using the log quadratic measure of dissimilarity relativeDissimilarity(CES_sigma_2, pvar = "prices", qvar="quantities", pervar = "time", prodID = "prodID", indexMethod="fisher", similarityMethod = "logquadratic") ```

IndexNumR documentation built on Feb. 7, 2022, 5:09 p.m.