The OpenD Programming Language

categoricalCDF

Computes the Categorical cumulative distribution function (CDF).

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

Parameters

x size_t: value to evaluate CDF
p Slice!(Iterator, 1, kind): slice containing the probability associated with the Categorical Distribution

Examples

import mir.ndslice.slice: sliced;
import mir.test: shouldApprox;

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

0.categoricalCDF(p).shouldApprox == 0.1;
1.categoricalCDF(p).shouldApprox == 0.6;
2.categoricalCDF(p).shouldApprox == 1.0;

Can also use dynamic array

import mir.test: shouldApprox;

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

0.categoricalCDF(p).shouldApprox == 0.1;
1.categoricalCDF(p).shouldApprox == 0.6;
2.categoricalCDF(p).shouldApprox == 1.0;

See Also

Categorical Distribution

Meta

Source

See Implementation

mir stat distribution categorical functions