mml

Class NormalMu

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.ByPdf

mml.Continuous

mml.NormalUPM

mml.NormalMu

All Implemented Interfaces:

java.lang.Comparable<Value>

public class NormalMu
extends NormalUPM

An UnParameterised Normal Model for cases where μ is the problem-defining parameter (common knowledge, given) and σ alone is the statistical parameter of the fully parameterised NormalMu.M to be estimated. We have the ready-made MML.NormalMu0 for the μ = 0 case. Also see NormalUPM and NormalUPM.M.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	NormalMu.Est The standard Estimator for a Normal Model with specified μ.
class	NormalMu.M M, a fully parameterised Normal Model with problem-defining parameter μ, and statistical parameter σ, as produced by the UnParameterised NormalMu.

Nested classes/interfaces inherited from class mml.Continuous

Continuous.Bounded, Continuous.Transform, Continuous.Uniform

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
double	mu The given, problem-defining parameter, μ, as a double.
protected Value.Cts	muC The given, problem-defining parameter, μ, as a Cts.

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
NormalMu(Value mu) μ is a given, the single problem-defining parameter.

Method Summary

Modifier and Type	Method and Description
NormalMu.M	apply(Value sigma) apply(σ), return Nμ,σ.
Value.Cts	defnParams() Return Real μ, the problem defining parameter.
UPModel.Est	estimator(Value ps) Return an Estimator of a fully parameterised Normal Model.
UPModel.Est	estimatorB(Value t) Return an Estimator of a fully parameterised Normal Model; note, t = triv! The Estimator calls NormalUPM.estSigma(la.la.Value, double, double, double) to estimate σ.
NormalMu.M	sp2Model(double msg1, double msg2, Value sigma) Given msg1, msg2 and the (one) statistical parameter, σ, return a fully parameterised Normal Model.

Methods inherited from class mml.NormalUPM

estSigma, ss, stats, stats, toString

Methods inherited from class mml.Continuous

transform

Methods inherited from class mml.UPModel

main, stats, stats, 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

muC

protected final Value.Cts muC

The given, problem-defining parameter, μ, as a Cts.

mu

public final double mu

The given, problem-defining parameter, μ, as a double.

Constructor Detail

NormalMu

public NormalMu(Value mu)

μ is a given, the single problem-defining parameter.

Method Detail

defnParams

public Value.Cts defnParams()

Return Real μ, the problem defining parameter.

Overrides:

defnParams in class UPModel

apply

public NormalMu.M apply(Value sigma)

apply(σ), return N_μ,σ.

Overrides:

apply in class NormalUPM

sp2Model

public NormalMu.M sp2Model(double msg1,
                           double msg2,
                           Value sigma)

Given msg1, msg2 and the (one) statistical parameter, σ, return a fully parameterised Normal Model.

Overrides:

sp2Model in class NormalUPM

estimator

public UPModel.Est estimator(Value ps)

Return an Estimator of a fully parameterised Normal Model. Note, ps = [σ_min, σ_max], the range for the std dev., σ. Also see NormalUPM.estimator(.).

Overrides:

estimator in class NormalUPM

estimatorB

public UPModel.Est estimatorB(Value t)

Return an Estimator of a fully parameterised Normal Model; note, t = triv! The Estimator calls NormalUPM.estSigma(la.la.Value, double, double, double) to estimate σ. If you require more control, e.g., of the prior, implement another Estimator. Also see estimator((lo,hi)).

Overrides:

estimatorB in class NormalUPM