mml

Class UPSeriesModel.Length.M

java.lang.Object

la.la.Value

mml.Model

mml.SeriesModel

mml.UPSeriesModel.M

mml.UPSeriesModel.Length.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Direct Known Subclasses:

Alignment.UPSame.M, Markov.M, UPSeriesModel.K.M

Enclosing class:

UPSeriesModel.Length

public abstract class UPSeriesModel.Length.M
extends UPSeriesModel.M

Fully parameterised Model of Series having an explicit Model of lengths (as opposed to a terminating Value/symbol). Also see UnParameterised UPSeriesModel.Length.

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 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)

Method Summary

Modifier and Type	Method and Description
abstract Model	lenMdl() Return the explicit, fully parameterised Model of lengths.
Value	lenStats(Vector seqs, int lo, int hi) Return lenMdl().stats(seqs,lo,hi) statistics on the lengths of seqs, a data-set of Vectors.
double	nlPr(Value sv) The negative log probability of datum Series sv is the sum of the nlPr of sv's length, and of sv's elements.
Vector	random() Generate a random Series, that is a Vector of a random length, with random contents, from the Model.

Methods inherited from class mml.UPSeriesModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.SeriesModel

analysis, asUPModel

Methods inherited from class mml.Model

asEstimator, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, nlLH, 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

Constructor Detail

M

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

Method Detail

lenMdl

public abstract Model lenMdl()

Return the explicit, fully parameterised Model of lengths.

nlPr

public double nlPr(Value sv)

The negative log probability of datum Series sv is the sum of the nlPr of sv's length, and of sv's elements.

Specified by:

nlPr in class SeriesModel

lenStats

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

Return lenMdl().stats(seqs,lo,hi) statistics on the lengths of seqs, a data-set of Vectors. This is used in stats(seqs). Also see UPSeriesModel.Length.lenStats(la.maths.Vector, int, int).

random

public Vector random()

Generate a random Series, that is a Vector of a random length, with random contents, from the Model. It needs lenMdl() and SeriesModel.Analysis.eltM() to implement random().

Overrides:

random in class Model