# ddlppar: Distance between discrete probability distributions given the... In dad: Three-Way / Multigroup Data Analysis Through Densities

 ddlppar R Documentation

## Distance between discrete probability distributions given the probabilities on their common support

### Description

L^p distance between two discrete probability distributions on the same support (which can be a Cartesian product of q sets) , given the probabilities of the states (which are q-tuples) of the support.

### Usage

ddlppar(p1, p2, p = 1)


### Arguments

 p1 array (or table) the dimension of which is q. The first probability distribution on the support. p2 array (or table) the dimension of which is q. The second probability distribution on the support. p integer. Parameter of the distance.

### Details

The L^p distance ||p_1 - p_2|| between two discrete distributions p_1 and p_2 is given by the formula:

||p_1 - p_2||^p = \sum_x{|p_1(x)-p_2(x)|^p}

If p=1, it is the variational distance.

If p=2, it is the Patrick-Fisher distance.

### Author(s)

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

### References

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

ddlp: L^p distance between two estimated discrete distributions, given samples.

Other distances: ddchisqsympar, ddhellingerpar, ddjeffreyspar, ddjensenpar.

### Examples

# Example 1
p1 <- array(c(1/2, 1/2), dimnames = list(c("a", "b")))
p2 <- array(c(1/4, 3/4), dimnames = list(c("a", "b")))
ddlppar(p1, p2)
ddlppar(p1, p2, p=2)

# 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")))
p1 <- table(x1)/nrow(x1)
p2 <- table(x2)/nrow(x2)
ddlppar(p1, p2)


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