mml

Class R_D.Independent

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.ByPdf

mml.R_D

mml.R_D.Independent

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

R_D

public static class R_D.Independent
extends R_D

A Vector of Models is a Model of Vectors R^D. The fully parameterised Model is R_D.Independent.M. Also see the Multivariate Model Independent.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	R_D.Independent.M A Vector of parameterised Continuous Models makes a parameterised Model of Continuous Vectors RD.

Nested classes/interfaces inherited from class mml.R_D

R_D.Forest, R_D.ForestSearch, R_D.Independent, R_D.NrmDir, R_D.Transform

Nested classes/interfaces inherited from class mml.UPModel

UPModel.Est

Nested classes/interfaces inherited from class la.la.Function.Native

Function.Native.WithInverse

Nested classes/interfaces inherited from class la.la.Function

Function.Cts2Cts, Function.Cts2Cts2Cts, Function.CtsD2CtsD, Function.HasInverse, Function.Native, Function.Native2, Function.Native3

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
int	D The number of columns of the data.
Continuous	upm The UnParameterised Model, upm, that will be used, in different parameterisations, to model each column of the data.

Fields inherited from class mml.UPModel

dp

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
Independent(Value dp) Problem defining parameters are dp=⟨@link #upm upm},D⟩.

Method Summary

Modifier and Type	Method and Description
int	D() D(), the dimension of the data-space RD.
UPModel.Est	estimator(Value ps) Use upm's estimator to estimate message lengths and statistical parameters for each column of the data.
R_D.Independent.M	sp2Model(double m1, double m2, Value sps) Given two-part message lengths msg1 & msg2, and statistical parameter sp, return a fully parameterised M-Model.
Vector	stats(boolean add, Value ss0, Value ss1) Combine each ith of the collections of D statistics, ss0 and ss1, as upm does.
Vector	stats(Vector ds, int lo, int hi) Return a Vector of statistics, one element for each (yet to be) parameterised instance of upm.

Methods inherited from class mml.R_D

ds2L1stats, ds2NorL1stats, ds2Nstats, transform

Methods inherited from class mml.UPModel

apply, defnParams, main, stats, stats, toString, transform

Methods inherited from class la.la.Function

bOp, fromBop, fromUop, type, uOp

Methods inherited from class la.la.Value

AoM, bOp, compareTo, cons, cts, elt, errMsg, error, force, isTuple, just, n, nElts, nlAoM, pair, print, quad, real, RTE, triple, tuple, UOE, x

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

upm

public final Continuous upm

The UnParameterised Model, upm, that will be used, in different parameterisations, to model each column of the data.

D

public final int D

The number of columns of the data.

Constructor Detail

Independent

public Independent(Value dp)

Problem defining parameters are dp=⟨@link #upm upm},D⟩.

Method Detail

D

public int D()

Description copied from class: R_D

D(), the dimension of the data-space R^D. R_D Models are of fixed-length Vectors of Cts, nElts()==D(). D() is logically part of the type of 'this'. You cannot count on learning D() from a data-set - it might be empty.

Specified by:

D in class R_D

sp2Model

public R_D.Independent.M sp2Model(double m1,
                                  double m2,
                                  Value sps)

Description copied from class: UPModel

Given two-part message lengths msg1 & msg2, and statistical parameter sp, return a fully parameterised M-Model. If 'this' UPModel produces a Model m, then sp2Model(m.msg1(), m.msg2(), m.statParams()) must be equivalent to m. Also see apply(sp).

Specified by:

sp2Model in class R_D

stats

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

Return a Vector of statistics, one element for each (yet to be) parameterised instance of upm.

Specified by:

stats in class UPModel

stats

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

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

Specified by:

stats in class UPModel

estimator

public UPModel.Est estimator(Value ps)

Use upm's estimator to estimate message lengths and statistical parameters for each column of the data. This estimator needs a Vector, ps, of estimator parameters because there may be different priors for each column.

Overrides:

estimator in class UPModel