mml

Class Poisson0UPM

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Discretes

mml.Poisson0UPM

All Implemented Interfaces:

java.lang.Comparable<Value>

public class Poisson0UPM
extends Discretes

The UnParameterised Poisson0 Model. For most purposes MML.Poisson0 and Poisson0UPM.M should be enough, with little need to call upon Poisson0UPM directly? (The '0' is to remind us that the Model is for integers ≥ 0.)

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Poisson0UPM.M The fully parameterised Poisson0 Model (probability distribution) on integers in [0, ∞); its one statistical parameter, α, is both the mean and variance.

Nested classes/interfaces inherited from class mml.Discretes

Discretes.Bounded, Discretes.Shifted, Discretes.Uniform

Nested classes/interfaces inherited from class mml.UPModel

UPModel.Est, UPModel.Transform

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
Poisson0UPM(Value t)

Method Summary

Modifier and Type	Method and Description
UPModel.Est	estimator(Value AA) The Estimator has a parameter, AA, the parameter and mean of the Exponential prior.
Poisson0UPM.M	sp2Model(double m1, double m2, Value alpha) Given m1, m2 and α, return a fully parameterised Poisson0.
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) Calculate the sufficient statistics, [N, sum, sum log factorials], of a data-set ds.
java.lang.String	toString() Return a String representation of 'this' UnParameterised Model, including its problem-defining parameters.

Methods inherited from class mml.Discretes

apply, NandSum, NandSum, shifted, shifted

Methods inherited from class mml.UPModel

defnParams, 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

Constructor Detail

Poisson0UPM

public Poisson0UPM(Value t)

Method Detail

sp2Model

public Poisson0UPM.M sp2Model(double m1,
                              double m2,
                              Value alpha)

Given m1, m2 and α, return a fully parameterised Poisson0.

Specified by:

sp2Model in class Discretes

stats

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

Calculate the sufficient statistics, [N, sum, sum log factorials], of a data-set ds. Note that N and sum are sufficient to estimate α but sum log factorials is needed for nlLH (and hence msg2).

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

estimator

public UPModel.Est estimator(Value AA)

The Estimator has a parameter, AA, the parameter and mean of the Exponential prior.

Overrides:

estimator in class UPModel

toString

public java.lang.String toString()

Description copied from class: UPModel

Return a String representation of 'this' UnParameterised Model, including its problem-defining parameters.

Overrides:

toString in class UPModel