mml

Class NearInverse

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.ByPdf

mml.Continuous

mml.NearInverse

All Implemented Interfaces:

java.lang.Comparable<Value>

public class NearInverse
extends Continuous

The UnParameterised NearInverse Model of positive reals, (0, ∞). We would sometimes like to use a prior, pdf(x) ~ 1/x, x>0, (then, e.g., 0.1+/-.005, 1.0+/-.05, 10.+/-.5, etc., would all have the same probability) but it is improper because 1/x integrates to infinity;. NearInverse is proper and close to 1/x, the smaller delta, > 0, is the closer. There is no estimator — the intended use is as a prior close to 1/x. See the fully parameterised model NearInverse.M.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	NearInverse.M The fully parameterised NearInverse Model of positive reals.

Nested classes/interfaces inherited from class mml.Continuous

Continuous.Bounded, Continuous.Transform, Continuous.Uniform

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 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
NearInverse(Value t)

Method Summary

Modifier and Type	Method and Description
NearInverse.M	sp2Model(double msg1, double msg2, Value sp) 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 sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false).
Vector	stats(Vector ds, int lo, int hi) Sufficient statistics, ss = stats(ds,lo,hi), of elements [lo,hi) of a data-set ds; here ss = ds.[lo,hi).

Methods inherited from class mml.Continuous

transform

Methods inherited from class mml.UPModel

apply, defnParams, estimator, 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

Constructor Detail

NearInverse

public NearInverse(Value t)

Method Detail

stats

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

Sufficient statistics, ss = stats(ds,lo,hi), of elements [lo,hi) of a data-set ds; here ss = ds.[lo,hi). More on stats here.

Specified by:

stats in class UPModel

stats

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

Description copied from class: UPModel

Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false). Also see stats(ds,lo,hi).

Specified by:

stats in class UPModel

sp2Model

public NearInverse.M sp2Model(double msg1,
                              double msg2,
                              Value sp)

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 Continuous