mml

Class BetaUPM.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.ByPdf.M

mml.Continuous.M

mml.BetaUPM.M

All Implemented Interfaces:

java.lang.Comparable<Value>, HasPdf

Enclosing class:

BetaUPM

public class BetaUPM.M
extends Continuous.M

The fully parameterised Beta Model (probability distribution).

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	alpha Shape parameters 'alpha' and 'beta'.
double	beta Shape parameters 'alpha' and 'beta'.

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 = ⟨alpha, beta⟩.

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 / Β(alpha, beta)} xalpha-1 (1-x)beta-1.
double	random_x() If X ~ Gamma(alpha, theta) and Y ~ Gamma(beta, theta) independently then (X/(X+Y)) ~ B(alpha, beta) -- van der Waerden, Mathematical Statistics, Springer, 1969, cited in wikip.

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

alpha

public final double alpha

Shape parameters 'alpha' and 'beta'.

beta

public final double beta

Shape parameters 'alpha' and 'beta'.

Constructor Detail

M

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

Statistical parameters, sp = ⟨alpha, beta⟩.

Method Detail

nlPdf_x

public double nlPdf_x(double x)

pdf(x) = {1 / Β(alpha, beta)} x^alpha-1 (1-x)^beta-1.

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()

If X ~ Gamma(alpha, theta) and Y ~ Gamma(beta, theta) independently then (X/(X+Y)) ~ B(alpha, beta) -- van der Waerden, Mathematical Statistics, Springer, 1969, cited in wikip.

Overrides:

random_x in class Continuous.M