mml

Class UPModel.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Direct Known Subclasses:

BestOf.M, ByPdf.M, Discretes.M, Graphs.M, Missing.M, Mixture.M, Model.Transform.M, Multinomial.M.Trials.TM, Multivariate.M, Permutation.M, Sequences.M, UPModel.Transform.M

Enclosing class:

UPModel

public abstract class UPModel.M
extends Model

A fully parameterised Model, M, nested within an UnParameterised UPModel. A subclass of Model that extends UPModel.M gets stats(ds...) "for free" from UPModel.stats(ds...) – if appropriate – similarly toString(). Also see 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 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) Given two-part message lengths, msg1 and msg2, and statistical parameter(s), sp, construct an M-Model.

Method Summary

Modifier and Type	Method and Description
Model	asGiven(double msg2) Calls asGiven(0,msg2).
Model	asGiven(double msg1, double msg2) Enables setting the first- and second-part message lengths, msg1 and msg2, after having estimated the statistical parameter(s) of a Model, say.
Value	stats(boolean add, Value ss0, Value ss1) By default, combine statisticses ss0 and ss1 using the stats(add,ss0,ss1) of the the enclosing UPModel.
Value	stats(Vector ds, int lo, int hi) Return sufficient statistics ss=stats(ds,lo,hi) of elements [lo, hi), lo inclusive to hi exclusive, of data-set 'ds' using the stats(ds,lo,hi) of the enclosing UPModel.
java.lang.String	toString() Return a String representation of 'this' fully parameterised Model.

Methods inherited from class mml.Model

asEstimator, asUPModel, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, nlLH, nlPr, pr, random, 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)

Given two-part message lengths, msg1 and msg2, and statistical parameter(s), sp, construct an M-Model.

Method Detail

stats

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

Return sufficient statistics ss=stats(ds,lo,hi) of elements [lo, hi), lo inclusive to hi exclusive, of data-set 'ds' using the stats(ds,lo,hi) of the enclosing UPModel. This is often appropriate, but not always, for example, see BestOf.M.stats(...). Note that ss=M.stats(ds...) must be enough to calculate M.nlLH(ss) but UPModel.stats(ds...) must be enough to estimate a fully parameterised M-Model. More on stats [here].

Specified by:

stats in class Model

stats

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

By default, combine statisticses ss0 and ss1 using the stats(add,ss0,ss1) of the the enclosing UPModel. This is often appropriate, but not always. Note, ss=M.stats(ds...) must be enough to calculate M.nlLH(ss) but UPModel.stats(ds...) must be enough to estimate a fully parameterised model. More on stats [here].

Specified by:

stats in class Model

asGiven

public Model asGiven(double msg2)

Calls asGiven(0,msg2).

Overrides:

asGiven in class Model

asGiven

public Model asGiven(double msg1,
                     double msg2)

Enables setting the first- and second-part message lengths, msg1 and msg2, after having estimated the statistical parameter(s) of a Model, say. Also see asGiven(msg2).

Overrides:

asGiven in class Model

toString

public java.lang.String toString()

Return a String representation of 'this' fully parameterised Model. The result includes the enclosing UnParameterised Model, with its problem defining parameters, and 'this' M-Model's statistical parameter(s).

Overrides:

toString in class Model