R: Estimate the distance cutoff for a specified neighbor rate

estimateDc {densityClust} | R Documentation

## Estimate the distance cutoff for a specified neighbor rate

### Description

This function calculates a distance cutoff value for a specific distance matrix that makes the average neighbor rate (number of points within the distance cutoff value) fall between the provided range. The authors of the algorithm suggests aiming for a neighbor rate between 1 and 2 percent, but also states that the algorithm is quite robust with regards to more extreme cases.

### Usage

    estimateDc(distance, neighborRateLow = 0.01, neighborRateHigh = 0.02)

### Arguments

`distance` | A distance matrix
`neighborRateLow` | The lower bound of the neighbor rate
`neighborRateHigh` | The upper bound of the neighbor rate

### Value

A numeric value giving the estimated distance cutoff value

### Note

If the number of points is larger than 448 (resulting in 100,128 pairwise distances), 100,128 distance pairs will be randomly selected to speed up computation time. Use `set.seed()` prior to calling `estimateDc` in order to ensure reproducable results.

### References

Rodriguez, A., & Laio, A. (2014). Clustering by fast search and find of density peaks. Science, 344(6191), 1492-1496. doi:10.1126/science.1242072

### Examples

    irisDist <- dist(iris[,1:4])
    estimateDc(irisDist)

[Package densityClust version 0.3 Index]