mml

Class Markov.M

java.lang.Object

la.la.Value

mml.Model

mml.SeriesModel

mml.UPSeriesModel.M

mml.UPSeriesModel.Length.M

mml.Markov.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Markov

public class Markov.M
extends UPSeriesModel.Length.M

Markov.M, the fully parameterised Markov Model, of a given order, for data [lwb, upb]^*. Also see the UnParameterised Markov Model.

Nested Class Summary

Nested classes/interfaces inherited from class mml.SeriesModel

SeriesModel.Analysis

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
MultiState.M[]	mdls mdls, MultiState Models, one per context.

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) sp = (lenMdl()'s, mdls').

Method Summary

Modifier and Type	Method and Description
SeriesModel.Analysis	analysis(Value.Scannable sv) Return the Analysis of a datum Series sv.
Model	lenMdl() Return the explicit, fully parameterised Model of lengths.
double	nlLH(Value ss) Given statistics, ss = stats(ds), of a data-set, ds, return the negative log likelihood of ds.
Value	stats(boolean add, Value ss0, Value ss1) Calls upon stats(add,.,) of lenMdl.
Value	stats(Vector seqs, int lo, int hi) Collect statistics, ss = stats(seqs,lo,hi), of a data-set, that is of a Vector of Vectors, seqs.

Methods inherited from class mml.UPSeriesModel.Length.M

lenStats, nlPr, random

Methods inherited from class mml.UPSeriesModel.M

asGiven, asGiven, toString

Methods inherited from class mml.SeriesModel

asUPModel

Methods inherited from class mml.Model

asEstimator, 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

mdls

public final MultiState.M[] mdls

mdls, MultiState Models, one per context.

Constructor Detail

M

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

sp = (lenMdl()'s, mdls').

Method Detail

lenMdl

public final Model lenMdl()

Description copied from class: UPSeriesModel.Length.M

Return the explicit, fully parameterised Model of lengths.

Specified by:

lenMdl in class UPSeriesModel.Length.M

stats

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

Collect statistics, ss = stats(seqs,lo,hi), of a data-set, that is of a Vector of Vectors, seqs. Calls upon lenMdl vai UPSeriesModel.Length.M.lenStats(la.maths.Vector, int, int).

Overrides:

stats in class UPSeriesModel.M

stats

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

Calls upon stats(add,.,) of lenMdl.

Overrides:

stats in class UPSeriesModel.M

nlLH

public double nlLH(Value ss)

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

Specified by:

nlLH in class Model

analysis

public SeriesModel.Analysis analysis(Value.Scannable sv)

Return the Analysis of a datum Series sv.

Specified by:

analysis in class SeriesModel