mml

Class Direction.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.ByPdf.M

mml.R_D.M

mml.Direction.M

All Implemented Interfaces:

java.lang.Comparable<Value>, HasPdf

Direct Known Subclasses:

Direction.Uniform.M, vMF.M

Enclosing class:

Direction

public abstract class Direction.M
extends R_D.M

(Abstract) a fully parameterised Model of Direction is made by defining nlPdf(v). The UnParameterised Model is Direction.

Nested Class Summary

Nested classes/interfaces inherited from class mml.R_D.M

R_D.M.Transform

Nested classes/interfaces inherited from class mml.Model

Model.Defaults

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)

Method Summary

Modifier and Type	Method and Description
abstract double	nlPdf(Value v) The negative log probability density of datum Vector v must be defined on the unit-radius K-sphere, the surface of a D-ball in RD, D=K+1.
double	nlPr(Value v) The negative log probability of datum Vector v; note that v need not be normalised but it is taken to be a Direction with v.norm() being "common knowledge".

Methods inherited from class mml.R_D.M

D, random_x, random, random, transform

Methods inherited from class mml.ByPdf.M

nlPr, pdf

Methods inherited from class mml.UPModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.Model

asEstimator, asUPModel, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, nlLH, pr, 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)

Method Detail

nlPdf

public abstract double nlPdf(Value v)

The negative log probability density of datum Vector v must be defined on the unit-radius K-sphere, the surface of a D-ball in R^D, D=K+1. Note, it is most general if nlPdf(v) does not require v to be normalised. The given nlPr(v) adjusts for v.norm(). (If you do require v to be normalised, some other code will be doing that and you'll still have to check it anyway!)

Specified by:

nlPdf in interface HasPdf

Specified by:

nlPdf in class ByPdf.M

nlPr

public double nlPr(Value v)

The negative log probability of datum Vector v; note that v need not be normalised but it is taken to be a Direction with v.norm() being "common knowledge". That leaves K() degrees of freedom. nlPr returns nlPdf(v) + v.nlAoM(), plus K() * log(v.norm()). E.g., K = D-1 = 3-1 = 2, norm = 8, implies plus 2×3 = 6 bits. This adjusts for the norm.

Overrides:

nlPr in class ByPdf.M