mml

Class R_D.Forest.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.ByPdf.M

mml.R_D.M

mml.R_D.Forest.M

All Implemented Interfaces:

java.lang.Comparable<Value>, HasPdf

Enclosing class:

R_D.Forest

public class R_D.Forest.M
extends R_D.M
implements HasPdf

Fully parameterised R_D.Forest-model. Each column may have at most one parent column.

Nested Class Summary

Nested classes/interfaces inherited from class mml.R_D.M

R_D.M.Transform

Nested classes/interfaces inherited from class mml.Model

Model.Defaults

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
Linear1.M[]	Lin1 There is one Linear1 model n Lin1[] per parent-ed column, in order.
NormalUPM.M[]	Nrml There is one Normal model in Nrml[] per parent-less column, in order.

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' is a pair, a Vector of parameters for Normal- and a Vector of parameters for Linear1-models.

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Negative log likelihood for data-set ds where ss=stats(ds).
double	nlPdf(Value v) Negative log probability density of a D-element datum v.
void	random(double[] xs) TODO random(xs) not yet tested???

Methods inherited from class mml.R_D.M

D, random_x, random, transform

Methods inherited from class mml.ByPdf.M

nlPr, nlPr, pdf

Methods inherited from class mml.UPModel.M

asGiven, asGiven, stats, stats, 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

Methods inherited from interface mml.HasPdf

pdf

Field Detail

Nrml

public final NormalUPM.M[] Nrml

There is one Normal model in Nrml[] per parent-less column, in order. Nrml.length = D-nChildren.

Lin1

public final Linear1.M[] Lin1

There is one Linear1 model n Lin1[] per parent-ed column, in order. Lin1.length = nChildren.

Constructor Detail

M

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

'sp' is a pair, a Vector of parameters for Normal- and a Vector of parameters for Linear1-models.

Method Detail

nlPdf

public double nlPdf(Value v)

Negative log probability density of a D-element datum v.

Specified by:

nlPdf in interface HasPdf

Specified by:

nlPdf in class ByPdf.M

nlLH

public double nlLH(Value ss)

Negative log likelihood for data-set ds where ss=stats(ds).

Specified by:

nlLH in class Model

random

public void random(double[] xs)

TODO random(xs) not yet tested???

Overrides:

random in class R_D.M