mml

Class Independent.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.Multivariate.M

mml.Independent.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Independent

public class Independent.M
extends Multivariate.M

A fully parameterised Model of Tuples made from a Tuple of independent Models by the UnParameterised Independent Model. Also see Dependent.M.

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[]	ms The sub-Models making 'this' Independent.M Model.

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 sps) Given two-part message lengths, msg1 and msg2, and a Tuple of statistical parameters, sps, construct a Model of Tuples from the upms.

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Given sufficient statistics, ss = stats(ds), of a data-set, ds, return the negative log likelihood of ds.
double	nlPr(Value d) The negative log probability of a Tuple-datum, 'd', where the elements (fields, components, columns) of d are modelled independently.
Value.Tuple	random() Return a random Tuple, assuming each of the sub-Models can play its part.
Value.Tuple	stats(boolean add, Value ss0, Value ss1) Calls upon the stats(,,) of the ms[].
Value.Tuple	stats(Vector ds, int lo, int hi) Given a multivariate data-set, ds, return statistics, ss, a Tuple of course, one element per sub-ms.

Methods inherited from class mml.Multivariate.M

functionModel, width

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

ms

public final Model[] ms

The sub-Models making 'this' Independent.M Model. Also see upms[].

Constructor Detail

M

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

Given two-part message lengths, msg1 and msg2, and a Tuple of statistical parameters, sps, construct a Model of Tuples from the upms.

Method Detail

nlPr

public double nlPr(Value d)

The negative log probability of a Tuple-datum, 'd', where the elements (fields, components, columns) of d are modelled independently.

Specified by:

nlPr in class Model

stats

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

Given a multivariate data-set, ds, return statistics, ss, a Tuple of course, one element per sub-ms. Note that the components of a datum are modelled independently so an element of ss depends on just the corresponding column of ds. May or may not equal Independent.stats(Vector,int,int). More on stats here.

Overrides:

stats in class UPModel.M

stats

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

Calls upon the stats(,,) of the ms[]. May or may not equal Independent.stats(boolean,Value,Value).

Overrides:

stats in class UPModel.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

random

public Value.Tuple random()

Return a random Tuple, assuming each of the sub-Models can play its part.

Overrides:

random in class Model