KurtosisAccumulator

struct KurtosisAccumulator(T, KurtosisAlgo kurtosisAlgo, Summation summation)
struct KurtosisAccumulator(T, KurtosisAlgo kurtosisAlgo, Summation summation)
struct KurtosisAccumulator(T, KurtosisAlgo kurtosisAlgo, Summation summation)
struct KurtosisAccumulator(T, KurtosisAlgo kurtosisAlgo, Summation summation)
struct KurtosisAccumulator(T, KurtosisAlgo kurtosisAlgo, Summation summation)
struct KurtosisAccumulator(T, KurtosisAlgo kurtosisAlgo, Summation summation)
struct KurtosisAccumulator (
T
KurtosisAlgo kurtosisAlgo
Summation summation
) if (
isMutable!T &&
kurtosisAlgo == KurtosisAlgo.hybrid
) {
struct Summator(T, Summation summation) via import mir.math.sum : elementType, Summator;;
eponymoustemplate isConvertibleToSlice(T) via import mir.ndslice.slice : isConvertibleToSlice, isSlice, Slice, SliceKind;;
eponymoustemplate isSlice(T) via import mir.ndslice.slice : isConvertibleToSlice, isSlice, Slice, SliceKind;;
alias Slice = mir_slice via import mir.ndslice.slice : isConvertibleToSlice, isSlice, Slice, SliceKind;;
alias SliceKind = mir_slice_kind via import mir.ndslice.slice : isConvertibleToSlice, isSlice, Slice, SliceKind;;
enum bool isInputRange(R, E); via import std.range : isInputRange;;
enum bool isIterable(T); via import std.traits : isIterable;;
alias S = Summator!(T, summation);
this(Slice!(Iterator, N, kind) slice);
this(SliceLike x);
this(Range range);
this(T x);
void put(Range r);
void put(T x);
void put(KurtosisAccumulator!(U, kurtAlgo, sumAlgo) v);
size_t count();
F centeredSumOfQuarts();
F centeredSumOfCubes();
F centeredSumOfSquares();
F scaledSumOfCubes(bool isPopulation);
F scaledSumOfQuarts(bool isPopulation);
F mean();
F variance(bool isPopulation);
F skewness(bool isPopulation);
F kurtosis(bool isPopulation, bool isRaw);
}

Constructors

this this(Slice!(Iterator, N, kind) slice)
this this(SliceLike x)
this this(Range range)
this this(T x)

Members

Aliases

S alias S = Summator!(T, summation)

Functions

centeredSumOfCubes F centeredSumOfCubes()
centeredSumOfQuarts F centeredSumOfQuarts()
centeredSumOfSquares F centeredSumOfSquares()
count size_t count()
kurtosis F kurtosis(bool isPopulation, bool isRaw)
mean F mean()
put void put(Range r)
put void put(T x)
put void put(KurtosisAccumulator!(U, kurtAlgo, sumAlgo) v)
scaledSumOfCubes F scaledSumOfCubes(bool isPopulation)
scaledSumOfQuarts F scaledSumOfQuarts(bool isPopulation)
skewness F skewness(bool isPopulation)
variance F variance(bool isPopulation)

Examples

hybrid

import mir.math.common: approxEqual, pow;
import mir.ndslice.slice: sliced;
import mir.test: shouldApprox;

auto x = [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 v = KurtosisAccumulator!(double, KurtosisAlgo.hybrid, Summation.naive)(x);
v.kurtosis(true, true).shouldApprox == (792.784119 / 12) / pow(54.765625 / 12, 2.0);
v.kurtosis(true, false).shouldApprox == (792.784119 / 12) / pow(54.765625 / 12, 2.0) - 3;
v.kurtosis(false, false).shouldApprox == (792.784119 / 12) / pow(54.765625 / 12, 2.0) * (11.0 * 13.0) / (10.0 * 9.0) - 3.0 * (11.0 * 11.0) / (10.0 * 9.0);
v.kurtosis(false, true).shouldApprox == (792.784119 / 12) / pow(54.765625 / 12, 2.0) * (11.0 * 13.0) / (10.0 * 9.0) - 3.0 * (11.0 * 11.0) / (10.0 * 9.0) + 3;

v.put(4.0);
v.kurtosis(true, true).shouldApprox == (745.608180 / 13) / pow(57.019231 / 13, 2.0);
v.kurtosis(true, false).shouldApprox == (745.608180 / 13) / pow(57.019231 / 13, 2.0) - 3;
v.kurtosis(false, false).shouldApprox == (745.608180 / 13) / pow(57.019231 / 13, 2.0) * (12.0 * 14.0) / (11.0 * 10.0) - 3.0 * (12.0 * 12.0) / (11.0 * 10.0);
v.kurtosis(false, true).shouldApprox == (745.608180 / 13) / pow(57.019231 / 13, 2.0) * (12.0 * 14.0) / (11.0 * 10.0) - 3.0 * (12.0 * 12.0) / (11.0 * 10.0) + 3;

The OpenD Programming Language

KurtosisAccumulator

Constructors

Members

Aliases

Functions

Examples

Meta

Source