VarianceAccumulator

struct VarianceAccumulator(T, VarianceAlgo varianceAlgo, Summation summation)
struct VarianceAccumulator(T, VarianceAlgo varianceAlgo, Summation summation)
struct VarianceAccumulator(T, VarianceAlgo varianceAlgo, Summation summation)
struct VarianceAccumulator(T, VarianceAlgo varianceAlgo, Summation summation)
struct VarianceAccumulator (
T
VarianceAlgo varianceAlgo
Summation summation
) if (
isMutable!T &&
varianceAlgo == VarianceAlgo.assumeZeroMean
) {
alias Slice = mir_slice via import mir.ndslice.slice : Slice, SliceKind, hasAsSlice;;
alias SliceKind = mir_slice_kind via import mir.ndslice.slice : Slice, SliceKind, hasAsSlice;;
template hasAsSlice(T) via import mir.ndslice.slice : Slice, SliceKind, hasAsSlice;;
Summator!(T, summation) centeredSumOfSquares;
this(Range r);
this(T x);
void put(Range r);
void put(T x);
void put(VarianceAccumulator!(T, varianceAlgo, summation) v);
size_t count();
F mean();
F variance(bool isPopulation);
}

Constructors

this this(Range r)
this this(T x)

Members

Functions

count size_t count()
mean F mean()
put void put(Range r)
put void put(T x)
put void put(VarianceAccumulator!(T, varianceAlgo, summation) v)
variance F variance(bool isPopulation)

Variables

centeredSumOfSquares Summator!(T, summation) centeredSumOfSquares;

Examples

import mir.math.common: approxEqual;
import mir.ndslice.slice: sliced;

auto a = [0.0, 1.0, 1.5, 2.0, 3.5, 4.25,
          2.0, 7.5, 5.0, 1.0, 1.5, 0.0].sliced;
auto x = a.center;

enum PopulationTrueCT = true;
enum PopulationFalseCT = false;
bool PopulationTrueRT = true;
bool PopulationFalseRT = false;

VarianceAccumulator!(double, VarianceAlgo.assumeZeroMean, Summation.naive) v;
v.put(x);

assert(v.variance(PopulationTrueRT).approxEqual(54.76562 / 12));
assert(v.variance(PopulationTrueCT).approxEqual(54.76562 / 12));
assert(v.variance(PopulationFalseRT).approxEqual(54.76562 / 11));
assert(v.variance(PopulationFalseCT).approxEqual(54.76562 / 11));

v.put(4.0);
assert(v.variance(PopulationTrueRT).approxEqual(70.76562 / 13));
assert(v.variance(PopulationTrueCT).approxEqual(70.76562 / 13));
assert(v.variance(PopulationFalseRT).approxEqual(70.76562 / 12));
assert(v.variance(PopulationFalseCT).approxEqual(70.76562 / 12));

import mir.math.common: approxEqual;
import mir.ndslice.slice: sliced;

auto a = [0.0, 1.0, 1.5, 2.0, 3.5, 4.25,
          2.0, 7.5, 5.0, 1.0, 1.5, 0.0].sliced;
auto b = a.center;
auto x = b[0 .. 6];
auto y = b[6 .. $];

enum PopulationTrueCT = true;
enum PopulationFalseCT = false;
bool PopulationTrueRT = true;
bool PopulationFalseRT = false;

VarianceAccumulator!(double, VarianceAlgo.assumeZeroMean, Summation.naive) v;
v.put(x);
assert(v.variance(PopulationTrueRT).approxEqual(13.492188 / 6));
assert(v.variance(PopulationTrueCT).approxEqual(13.492188 / 6));
assert(v.variance(PopulationFalseRT).approxEqual(13.492188 / 5));
assert(v.variance(PopulationFalseCT).approxEqual(13.492188 / 5));

v.put(y);
assert(v.variance(PopulationTrueRT).approxEqual(54.76562 / 12));
assert(v.variance(PopulationTrueCT).approxEqual(54.76562 / 12));
assert(v.variance(PopulationFalseRT).approxEqual(54.76562 / 11));
assert(v.variance(PopulationFalseCT).approxEqual(54.76562 / 11));

The OpenD Programming Language

VarianceAccumulator

Constructors

Members

Functions

Variables

Examples

Meta

Source