# diss: Calculate the dissimilarity matrix between two datasets of... In provenance: Statistical Toolbox for Sedimentary Provenance Analysis

 diss.distributional R Documentation

## Calculate the dissimilarity matrix between two datasets of class `distributional`, `compositional`, `counts` or `varietal`

### Description

Calculate the dissimilarity matrix between two datasets of class `distributional` or `compositional` using the Kolmogorov-Smirnov, Sircombe-Hazelton, Aitchison or Bray-Curtis distance

### Usage

``````## S3 method for class 'distributional'
diss(x, method = NULL, log = FALSE, verbose = FALSE, ...)

## S3 method for class 'compositional'
diss(x, method = NULL, ...)

## S3 method for class 'counts'
diss(x, method = NULL, ...)

## S3 method for class 'varietal'
diss(x, method = NULL, ...)
``````

### Arguments

 `x` an object of class `distributional`, `compositional` or `counts` `method` if `x` has class `distributional`: either `"KS"`, `"Wasserstein"`, `"Kuiper"` or `"SH"`; if `x` has class `compositional`: either `"aitchison"` or `"bray"`; if `x` has class `counts`: either `"chisq"` or `"bray"`; if `x` has class `varietal`: either `"KS"`, `"W2_1D"` or `"W2"`. `log` logical. If `TRUE`, subjects the distributional data to a logarithmic transformation before calculating the Wasserstein distance. `verbose` logical. If `TRUE`, gives progress updates during the construction of the dissimilarity matrix. `...` optional arguments

### Details

`"KS"` stands for the Kolmogorov-Smirnov statistic, `"W2_1D"` for the 1-dimensional Wasserstein-2 distance, `"Kuiper"` for the Kuiper statistic, `"SH"` for the Sircombe-Hazelton distance, `"aitchison"` for the Aitchison logratio distance, `"bray"` for the Bray-Curtis distance, `"chisq"` for the Chi-square distance, and "W2" for the 2-dimensional Wasserstein-2 distance.

### Value

an object of class `diss`

``````data(Namib)