mml

Class MultiState.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.Discretes.M

mml.Discretes.Bounded.M

mml.MultiState.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

MultiState

public class MultiState.M
extends Discretes.Bounded.M

A fully parameterised MultiState (Multinomial) Model; also see the UnParameterised MultiState Model. The statistical parameters is a Vector of probabilities, which must be (L1-) normalised. This is checked!

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 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 prs) The statistical parameters, prs, are the probabilities.

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Given sufficient statistics, ss = stats(ds), of a data-set, ds, return nlLH(ss), the negative log LikeliHood (negative log probability) of ds.
double	nlPr_n(int dn) Return nlPrs[dn-lwb_n()].
double	pr_n(int dn) Return prs[dn-lwb_n()].

Methods inherited from class mml.Discretes.Bounded.M

asUPModel, bounds, lwb_n, lwb, random_n, random, random, randomSeries, type, upb_n, upb

Methods inherited from class mml.Discretes.M

nlPr, pr, shifted

Methods inherited from class mml.UPModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.Model

asEstimator, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, statParams, stats, stats, sumNlPr, transform, 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

Constructor Detail

M

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

The statistical parameters, prs, are the probabilities. It is required that ∑ prs[i] = 1.

Method Detail

pr_n

public double pr_n(int dn)

Return prs[dn-lwb_n()].

Overrides:

pr_n in class Discretes.M

nlPr_n

public double nlPr_n(int dn)

Return nlPrs[dn-lwb_n()].

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 nlLH(ss), the negative log LikeliHood (negative log probability) of ds.

Specified by:

nlLH in class Model