mml

Class R_D.Independent.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.ByPdf.M

mml.R_D.M

mml.R_D.Independent.M

All Implemented Interfaces:

java.lang.Comparable<Value>, HasPdf

Enclosing class:

R_D.Independent

public class R_D.Independent.M
extends R_D.M

A Vector of parameterised Continuous Models makes a parameterised Model of Continuous Vectors R^D. The UnParameterised Model is R_D.Independent.

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
Continuous.M[]	mdls One parameterised upm-Model, mdls[i], per column of the data.

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) Statistical parameters, sps, is a Vector of statistical parameters, one per mdls[i].

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	nlPdf(Value d) The negative log pdf(d) where d is a datum, a member of RD.
Vector	random() Return a random (exact) Vector in RD, one element per mdls[i].
Vector	stats(boolean add, Value ss0, Value ss1) Combine each ith of the collections of D statistics, ss0 and ss1, as mdls[.] does.
Vector	stats(Vector ds, int lo, int hi) Return a Vector of statisticses, one element per parameterised sub-model mdls[.].

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, 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

mdls

public final Continuous.M[] mdls

One parameterised upm-Model, mdls[i], per column of the data.

Constructor Detail

M

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

Statistical parameters, sps, is a Vector of statistical parameters, one per mdls[i].

Method Detail

nlPdf

public double nlPdf(Value d)

The negative log pdf(d) where d is a datum, a member of R^D.

Specified by:

nlPdf in interface HasPdf

Specified by:

nlPdf in class ByPdf.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. This is done column-wise by mdls[i].

Specified by:

nlLH in class Model

stats

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

Return a Vector of statisticses, one element per parameterised sub-model mdls[.].

Overrides:

stats in class UPModel.M

stats

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

Combine each i^th of the collections of D statistics, ss0 and ss1, as mdls[.] does.

Overrides:

stats in class UPModel.M

random

public Vector random()

Return a random (exact) Vector in R^D, one element per mdls[i].

Overrides:

random in class R_D.M