calcDS: Calculates discrimination score (DS)

In IDmeasurer: Assessment of Individual Identity in Animal Signals

Description

This function will take the specified data frame and will perform linear discrimination analysis with leave-one-out crossvalidation and equal priors for each individual (e.g., all priors will be set to 1/10 in case that the dataset contains 10 individuals). Variables are not modified in any way; scaling, centering, transformation of variables, or principal component analysis, etc., if required, need to be done on dataset before calling this function.

Reference: e.g. Hafner, G. W., Hamilton, C. L., Steiner, W. W., Thompson, T. J., & Winn, H. E. (1979). Signature information in the song of the humpback whale. Journal of the Acoustical Society of America, 66, 1-6. doi:10.1121/1.383072

Usage

calcDS(df)

Arguments

df	A data frame with the first column noting individual identity of the sample.

Value

Proportion of samples correctly classified by LDA in df.

See Also

Other individual identity metrics: calcF, calcHM, calcHSngroups, calcHSnpergroup, calcHSntot, calcHSvarcomp, calcHS, calcMI, calcPICbetweenmeans, calcPICbetweentot, calcPIC

Examples

calcDS(ANmodulation)

IDmeasurer documentation built on May 9, 2019, 5:02 p.m.