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

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

Arguments

object

A list of ctmm fit objects to compare.

method

Square distance measure to return: "Bhattacharyya", "Mahalanobis", or "Euclidean".

level

The confidence level desired for the output.

debias

Approximate debiasing of the square distance.

...

Not currently used.

Value

A table of confidence intervals on the square distance estimate. 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. The square Mahalanobis and Bhattacharyya distances are unitless.

Author

C. H. Fleming

Note

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

See also

Examples

# \donttest{ # Load package and data 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)
#> , , low #> #> Cilla Gabs #> Cilla 0 0 #> Gabs 0 0 #> #> , , est #> #> Cilla Gabs #> Cilla 0.000000000 0.004452928 #> Gabs 0.004452928 0.000000000 #> #> , , high #> #> Cilla Gabs #> Cilla 0.0000000 0.6575691 #> Gabs 0.6575691 0.0000000 #>
# }