mml

Class GammaUPM.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.ByPdf.M

mml.Continuous.M

mml.GammaUPM.M

All Implemented Interfaces:

java.lang.Comparable<Value>, HasPdf

Enclosing class:

GammaUPM

public class GammaUPM.M
extends Continuous.M

The fully parameterised γ Model (probability distribution). Also see MML.Gamma and GammaUPM.

Nested Class Summary

Nested classes/interfaces inherited from class mml.Continuous.M

Continuous.M.Transform

Nested classes/interfaces inherited from class mml.Model

Model.Defaults

Nested classes/interfaces inherited from class la.la.Value

Value.Atomic, Value.Bool, Value.Char, Value.Chars, Value.Cts, Value.Defer, Value.Discrete, Value.Enum, Value.Inc_Or, Value.Int, Value.Lambda, Value.List, Value.Maybe, Value.Option, Value.Real, Value.Scannable, Value.Structured, Value.Triv, Value.Tuple

Field Summary

Fields

Modifier and Type	Field and Description
double	k Shape parameter 'k', and scale parameter θ (theta).
double	theta Shape parameter 'k', and scale parameter θ (theta).

Fields inherited from class mml.Model

msg1, msg2, sp

Fields inherited from class la.la.Value

C, comparator, CR, E, eight, ffalse, five, fiveR, four, fourR, half, negCR, negOne, negOneR, negTenR, nilVal, nine, None, one, oneR, PI, PIby2, point01, point1, point5, point9, quarter, seven, six, ten, tenR, three, threeR, triv, ttrue, two, twoR, zero, zeroR

Constructor Summary

Constructors

Constructor and Description
M(double msg1, double msg2, Value sp) Statistical parameters, sp = ⟨k, θ⟩.

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Assumes that statistics are the data-set itself.
double	nlPdf_x(double x) pdf(x) = {1 / (Γ(k) θk)} xk-1 e-x/θ.
double	random_x() See Marsaglia & Tsang, A simple method for generating Gamma variables, ACM Trans on Math Software, 26(3), 363-372, 2000.

Methods inherited from class mml.Continuous.M

nlPdf, random_x, random, random, random, transform

Methods inherited from class mml.ByPdf.M

nlPr, nlPr, pdf

Methods inherited from class mml.UPModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.Model

asEstimator, asUPModel, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, pr, random, randomSeries, statParams, stats, stats, sumNlPr, transform, type, zeroTriv

Methods inherited from class la.la.Value

AoM, apply, bOp, compareTo, cons, cts, elt, errMsg, error, force, isTuple, just, main, n, nElts, nlAoM, pair, print, quad, real, RTE, triple, tuple, UOE, uOp, x

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

k

public final double k

Shape parameter 'k', and scale parameter θ (theta).

theta

public final double theta

Shape parameter 'k', and scale parameter θ (theta).

Constructor Detail

M

public M(double msg1,
         double msg2,
         Value sp)

Statistical parameters, sp = ⟨k, θ⟩.

Method Detail

nlPdf_x

public double nlPdf_x(double x)

pdf(x) = {1 / (Γ(k) θ^k)} x^k-1 e^-x/θ.

Specified by:

nlPdf_x in class Continuous.M

nlLH

public double nlLH(Value ss)

Assumes that statistics are the data-set itself.

Specified by:

nlLH in class Model

random_x

public double random_x()

See Marsaglia & Tsang, A simple method for generating Gamma variables, ACM Trans on Math Software, 26(3), 363-372, 2000. See especially pages 369 to 371.

Overrides:

random_x in class Continuous.M