The OpenD Programming Language

categoricalLPMF

Computes the Categorical log probability mass function (LPMF).

elementType!(Slice!(Iterator, 1, kind)) categoricalLPMF(size_t x, Slice!(Iterator, 1, kind) p)
T categoricalLPMF(size_t x, T[] p)
@safe pure nothrow @nogc
T
categoricalLPMF
(
T
)
(
const size_t x
,
scope const T[] p...
)
if (
isFloatingPoint!T
)

Parameters

x size_t: value to evaluate LPMF
p T[]: slice containing the probability associated with the Categorical Distribution

Examples

import mir.math.common: log;
import mir.ndslice.slice: sliced;
import mir.test: shouldApprox;

static immutable x = [0.1, 0.5, 0.4];
auto p = x.sliced;

0.categoricalLPMF(p).shouldApprox == log(0.1);
1.categoricalLPMF(p).shouldApprox == log(0.5);
2.categoricalLPMF(p).shouldApprox == log(0.4);

Can also use dynamic array

import mir.math.common: log;
import mir.test: shouldApprox;

double[] p = [0.1, 0.5, 0.4];

0.categoricalLPMF(p).shouldApprox == log(0.1);
1.categoricalLPMF(p).shouldApprox == log(0.5);
2.categoricalLPMF(p).shouldApprox == log(0.4);

See Also

Categorical Distribution

Meta

Source

See Implementation

mir stat distribution categorical functions