mml

Class CPT.M

java.lang.Object

la.la.Value

mml.Model

mml.FunctionModel

mml.UPFunctionModel.M

mml.CPT.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

CPT

public class CPT.M
extends UPFunctionModel.M

CPT.M, a fully parameterised Function Model, being a conditional probability table. The UnParameterised Function Model is CPT.

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
Model[]	condMdls An array of now fully parameterised (conditional) upm-Models, one Model for each possible case (Value) of the input datum.

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, Vector sps) Given (m1,m2,sps), where sps is a Vector of statistical parameters, one for each entry of the CPT, construct the fully parameterised CPT.

Method Summary

Modifier and Type	Method and Description
Model	condModel(Value id) Return the Model of the ouput datum conditional upon the Value of the input datum (variable), 'id'.
double	nlLH(Value ss) Given sufficient statistics, ss = stats(ds), of a data-set, ds, return the negative log likelihood of ds.
Vector	stats(boolean add, Value ss0, Value ss1) Calls upon condMdls[.].stats(add,.,.).
Vector	stats(Vector ds, int lo, int hi) Given a data-set, ds, calculate statistics (of the output datum) for each case (Value) of the input datum.

Methods inherited from class mml.UPFunctionModel.M

asGiven, asGiven, toString

Methods inherited from class mml.FunctionModel

asUPModel, condNl2Pr, condNlPr, condPr, nlPr, pr, random, random

Methods inherited from class mml.Model

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

condMdls

public final Model[] condMdls

An array of now fully parameterised (conditional) upm-Models, one Model for each possible case (Value) of the input datum.

Constructor Detail

M

public M(double msg1,
         double msg2,
         Vector sps)

Given (m1,m2,sps), where sps is a Vector of statistical parameters, one for each entry of the CPT, construct the fully parameterised CPT. Also see condMdls.

Method Detail

condModel

public Model condModel(Value id)

Return the Model of the ouput datum conditional upon the Value of the input datum (variable), 'id'. The kind of Model that can returned is arbitrary, as specified by CPT; it is not restricted to MultiState Models.

Specified by:

condModel in class FunctionModel

stats

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

Given a data-set, ds, calculate statistics (of the output datum) for each case (Value) of the input datum. Uses condMdls[.]stats(.,.,.,.,.). More on stats here.

Overrides:

stats in class UPFunctionModel.M

stats

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

Calls upon condMdls[.].stats(add,.,.).

Overrides:

stats in class UPFunctionModel.M

nlLH

public double nlLH(Value ss)

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

Specified by:

nlLH in class Model