mml

Class BestOf.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.BestOf.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

BestOf

public class BestOf.M
extends UPModel.M

The fully parameterised Model; BestOf is the UnParameterised Model.

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
int	choice The index of the best of the upms[] (parameterised).
Model	mdl The fully parameterised upms[choice]-Model, the best choice out of the upms[].

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) Two part message lengths, msg1 and msg2, and statistical parameter(s) sp=⟨i,spi⟩.

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Given sufficient statistics, ss=stats(ds), of a data-set ds, return mdl's negative log LikeliHood of ds.
double	nlPr(Value d) Return mdl's negative log probability of data 'd'.
Value	random() Return a Value from mdl.
Value	stats(boolean add, Value ss0, Value ss1) Return mdl's stats ss0±ss1, "+" if add is true otherwise "-".
Value	stats(Vector ds, int lo, int hi) Return mdl's stats for ds[lo,hi).

Methods inherited from class mml.UPModel.M

asGiven, asGiven, 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

choice

public int choice

The index of the best of the upms[] (parameterised).

mdl

public Model mdl

The fully parameterised upms[choice]-Model, the best choice out of the upms[].

Constructor Detail

M

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

Two part message lengths, msg1 and msg2, and statistical parameter(s) sp=⟨i,sp_i⟩. 'i' is the index of the best Model out of umps[]. 'sp_i' is the statistical parameter(s) for that Model.

Method Detail

nlPr

public double nlPr(Value d)

Return mdl's negative log probability of data 'd'.

Specified by:

nlPr in class Model

stats

public Value stats(Vector ds,
                   int lo,
                   int hi)

Return mdl's stats for ds[lo,hi). Also see BestOf.stats(...)) which is more extensive.

Overrides:

stats in class UPModel.M

stats

public Value stats(boolean add,
                   Value ss0,
                   Value ss1)

Return mdl's stats ss0±ss1, "+" if add is true otherwise "-". Also see BestOf.stats(...)).

Overrides:

stats in class UPModel.M

nlLH

public double nlLH(Value ss)

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

Specified by:

nlLH in class Model

random

public Value random()

Return a Value from mdl.

Overrides:

random in class Model