mml

Class Geometric0UPM

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Discretes

mml.Geometric0UPM

All Implemented Interfaces:

java.lang.Comparable<Value>

public class Geometric0UPM
extends Discretes

The UnParameterised Geometric0 Model. For most purposes MML.Geometric0 and Geometric0UPM.M should be enough, with little or no need to call upon Geometric0UPM 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	Geometric0UPM.M The fully parameterised Geometric Model (probability distribution) on integers in [0, ∞); the mean, μ, is its one statistical-parameter.

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
Geometric0UPM(Value t)

Method Summary

Modifier and Type	Method and Description
UPModel.Est	estimator(Value AA) The Estimator has a parameter, 'AA', the parameter of the Exponential prior on the mean of the Geometric distribution.
Geometric0UPM.M	sp2Model(double m1, double m2, Value mu) Given m1, m2 and μ return a fully parameterised Geometric 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) Returns NandSum(ds,lo,hi).
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

Geometric0UPM

public Geometric0UPM(Value t)

Method Detail

sp2Model

public Geometric0UPM.M sp2Model(double m1,
                                double m2,
                                Value mu)

Given m1, m2 and μ return a fully parameterised Geometric Model.

Specified by:

sp2Model in class Discretes

stats

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

Returns NandSum(ds,lo,hi). More on statistics 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

estimator

public UPModel.Est estimator(Value AA)

The Estimator has a parameter, 'AA', the parameter of the Exponential prior on the mean of the Geometric distribution.

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