mml

Class Geometric0UPM.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.Discretes.M

mml.Geometric0UPM.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Geometric0UPM

public class Geometric0UPM.M
extends Discretes.M

The fully parameterised Geometric Model (probability distribution) on integers in [0, ∞); the mean, μ, is its one statistical-parameter. Also see the UnParameterised MML.Geometric0 and class Geometric0UPM for estimation etc., and [www].

Nested Class Summary

Nested classes/interfaces inherited from class mml.Model

Model.Defaults, Model.Transform

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	mu Statistical parameter μ, the mean, as a double.

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 mu)

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Given sufficient statistics, ss = stats(ds), of a data-set ds, return the negative log LikeliHood of ds.
double	nlPr_n(int n) The negative log probability of n; note, n≥0.
int	random_n() ???random_n() could be made much(!) more efficient!!! This implementation is just for completeness!
Value.Int	random() Return a random number from 'this' Geometric distribution; calls random_n().

Methods inherited from class mml.Discretes.M

nlPr, pr_n, pr, shifted

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, 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

mu

public final double mu

Statistical parameter μ, the mean, as a double.

Constructor Detail

M

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

Method Detail

nlPr_n

public double nlPr_n(int n)

The negative log probability of n; note, n≥0.

Specified by:

nlPr_n in class Discretes.M

nlLH

public double nlLH(Value ss)

Given sufficient statistics, ss = stats(ds), of a data-set ds, return the negative log LikeliHood of ds.

Specified by:

nlLH in class Model

random

public Value.Int random()

Return a random number from 'this' Geometric distribution; calls random_n().

Overrides:

random in class Model

random_n

public int random_n()

???random_n() could be made much(!) more efficient!!! This implementation is just for completeness!

Specified by:

random_n in class Discretes.M