# distance: Calculate the square distance between two distributions or... In ctmm: Continuous-Time Movement Modeling

 distance R Documentation

## Calculate the square distance between two distributions or location estimates

### Description

This function calculates various square distances measures between distributions, including the, Bhattacharyya distance, Mahalanobis distance, and Euclidean distance.

### Usage

`` distance(object,method="Mahalanobis",sqrt=FALSE,level=0.95,debias=TRUE,...) ``

### Arguments

 `object` A `list` of `ctmm` fit objects or single-location `telemetry` objects to compare. `method` Square distance measure to return: `"Bhattacharyya"`, `"Mahalanobis"`, or `"Euclidean"`. `sqrt` Return the linear distance. `level` The confidence level desired for the output. `debias` Approximate debiasing of the square distance. `...` Not currently used.

### Value

A list with tables `DOF`, containing the effective samples sizes of the estimates, and `CI`, containing the confidence intervals of the distance estimates. A value of `0` implies that the two distributions have the same mean location, while larger values imply that the two distributions are farther apart. The (square) Euclidean distance has units of square meters, if `sqrt=FALSE`. The square Mahalanobis and Bhattacharyya distances are unitless. For the Euclidean distance, only the centroids are compared.

### Note

The Bhattacharyya distance (BD) is naturally of a squared form and is not further squared.

### Author(s)

C. H. Fleming

`ctmm.fit`, `overlap`

### Examples

``````
library(ctmm)
data(buffalo)

# fit models for first two buffalo
GUESS <- lapply(buffalo[1:2], function(b) ctmm.guess(b,interactive=FALSE) )
# using ctmm.fit here for speed, but you should almost always use ctmm.select
FITS <- lapply(1:2, function(i) ctmm.fit(buffalo[[i]],GUESS[[i]]) )
names(FITS) <- names(buffalo[1:2])

# Mahalanobis distance between these two buffalo
distance(FITS)
``````

ctmm documentation built on Sept. 24, 2023, 1:06 a.m.