JSD: Calculate the Jensen-Shannon divergence (JSD)

In LDLcalc: Calculate and Predict the Low Density Lipoprotein Values

Calculate the Jensen-Shannon divergence (JSD)

Description

Calculate the Jensen-Shannon divergence between the same parameter of different data sets. This works only for two distributions.

Usage

JSD(vec1, vec2)

Arguments

vec1	The vector containing the values of the first data set.
vec2	The vector containing the values of the second data set.

Value

The function returns the value of the Jensen-Shannon divergence (JSD), the frequencies of the two datasets (freq1, freq2, dfFreqs) and the probabilities of the frequencies of the two groups, which should sum up to 1.

References

D.M. Endres, J.E. Schindelin, A new metric for probability distributions, IEEE Trans. Inf. Theory (2003), https://doi.org/10.1109/TIT.2003.813506.

F. Oesterreicher, I. Vajda, A new class of metric divergences on probability spaces and its applicability in statistics, Ann. Inst. Stat. Math. (2003), https://doi.org/ 10.1007/BF02517812.

Examples

## Not run: 
JSDCalc = JSD(model[["trainData"]]$LDLd,model[["testData"]]$LDLd)

## End(Not run)

LDLcalc documentation built on May 31, 2022, 5:07 p.m.