.classwiseMahalanobisRain {twoddpcr} | R Documentation

## Fuzzy clusters by bivariate normal distributions.

### Description

Assume that the class `cl` is bivariate normally distributed. This method adds fuzziness to the class. Other classes are not changed.

### Usage

    .classwiseMahalanobisRain(droplets, cl, maxDistance = 30, classCol = "class")

### Arguments

`droplets` | A data frame of droplets with `Ch1.Amplitude` and `Ch2.Amplitude` columns, as well as a class column (see the parameter `classCol`).
`cl` | The class to focus on. This should be either "NN", "NP", "PN" or "PP".
`maxDistance` | An integer corresponding to the maximum Mahalanobis distance for which we will consider points to be members of the class, i.e. this is the level outside of which we consider droplets to be too far from the cluster.
`classCol` | The column (name or number) from `droplets` representing the class.

### Value

A factor corresponding to the class column with `Rain` entries added for the class `cl`.

### Author(s)

Anthony Chiu, anthony.chiu@cruk.manchester.ac.uk

[Package twoddpcr version 1.16.0 Index]