ddhellinger: Distance between probability distributions of discrete... In dad: Three-Way / Multigroup Data Analysis Through Densities

 ddhellinger R Documentation

Distance between probability distributions of discrete variables given samples

Description

Hellinger (or Matusita) distance between two multivariate (`q > 1`) or univariate (`q = 1`) discrete probability distributions, estimated from samples.

Usage

``````ddhellinger(x1, x2)
``````

Arguments

 `x1, x2` data frames of `q` columns or vectors (can also be tibbles). If they are data frames and have not the same column names, there is a warning.

Details

Let `p_1` and `p_2` denote the estimated probability distributions of the discrete samples `x_1` and `x_2`. The Matusita distance between the discrete probability distributions of the samples are computed using the `ddhellingerpar` function.

Value

The distance between the two probability distributions.

Author(s)

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard

References

Deza, M.M. and Deza E. (2013). Encyclopedia of distances. Springer.

`ddhellingerpar`: Hellinger metric (Matusita distance) between two discrete distributions, given the on their common support probabilities.

Other distances: `ddchisqsym`, `ddjeffreys`, `ddjensen`, `ddlp`.

Examples

``````# Example 1
x1 <- c("A", "A", "B", "B")
x2 <- c("A", "A", "A", "B", "B")
ddhellinger(x1, x2)

# Example 2
x1 <- data.frame(x = factor(c("A", "A", "A", "B", "B", "B")),
y = factor(c("a", "a", "a", "b", "b", "b")))
x2 <- data.frame(x = factor(c("A", "A", "A", "B", "B")),
y = factor(c("a", "a", "b", "a", "b")))
ddhellinger(x1, x2)
``````

dad documentation built on Aug. 30, 2023, 5:06 p.m.