mml

Class LogStar0UPM.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.Discretes.M

mml.LogStar0UPM.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

LogStar0UPM

public class LogStar0UPM.M
extends Discretes.M

Model logStar0 should be enough for most purposes, but here are the classes, fully (trivially) parameterised (M) and UnParameterised (LogStar0UPM).

Nested Class Summary

Nested classes/interfaces inherited from class mml.Model

Model.Defaults, Model.Transform

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.Model

msg1, msg2, sp

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
M(double msg1, double msg2, Value sp) Note, requires msg1=0 and sp=triv.

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) Assumes that statistics are the data-set itself.
double	nlPr_n(int n) Negative log probability of datum int, n ≥ 0.
int	random_n() random_n() is not supported.
java.lang.String	toString() Return a String representation of 'this' fully parameterised Model.

Methods inherited from class mml.Discretes.M

nlPr, pr_n, pr, shifted

Methods inherited from class mml.UPModel.M

asGiven, asGiven, stats, stats

Methods inherited from class mml.Model

asEstimator, asUPModel, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, random, random, randomSeries, statParams, stats, stats, sumNlPr, transform, type, zeroTriv

Methods inherited from class la.la.Value

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

Methods inherited from class java.lang.Object

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

Constructor Detail

M

public M(double msg1,
         double msg2,
         Value sp)

Note, requires msg1=0 and sp=triv.

Method Detail

nlPr_n

public double nlPr_n(int n)

Negative log probability of datum int, n ≥ 0.

Specified by:

nlPr_n in class Discretes.M

nlLH

public double nlLH(Value ss)

Assumes that statistics are the data-set itself.

Specified by:

nlLH in class Model

random_n

public int random_n()

random_n() is not supported.

Specified by:

random_n in class Discretes.M

toString

public java.lang.String toString()

Description copied from class: UPModel.M

Return a String representation of 'this' fully parameterised Model. The result includes the enclosing UnParameterised Model, with its problem defining parameters, and 'this' M-Model's statistical parameter(s).

Overrides:

toString in class UPModel.M