mml

Class ExponentialUPM.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.ByPdf.M

mml.Continuous.M

mml.ExponentialUPM.M

All Implemented Interfaces:

java.lang.Comparable<Value>, HasPdf

Enclosing class:

ExponentialUPM

public class ExponentialUPM.M
extends Continuous.M

The fully parameterised (negative-) Exponential Model, has statistical parameter A, its mean. Its variance equals A². (In some texts it is parameterised with λ=1/A.)

Nested Class Summary

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

Continuous.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

Modifier and Type	Field and Description
double	A Statistical parameter 'A', the mean.

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 A) Note that A is the mean (and standard deviation).

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) See stats(...) of a data-set ds; for N data, {xi}, nlLH = N.log A + (1/A) ∑ xi.
double	nlPdf_x(double x) The pdf is 1/A e-x/A, for x≥0.
double	random_x() Return random double from this Model, that is A*times;log(x), where x is uniform in [0,1).

Methods inherited from class mml.Continuous.M

nlPdf, random_x, random, random, random, transform

Methods inherited from class mml.ByPdf.M

nlPr, 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, 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

Field Detail

A

public final double A

Statistical parameter 'A', the mean.

Constructor Detail

M

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

Note that A is the mean (and standard deviation).

Method Detail

nlPdf_x

public double nlPdf_x(double x)

The pdf is ¹/_A e^-x/A, for x≥0. Its negative log is x / A + log A.

Specified by:

nlPdf_x in class Continuous.M

nlLH

public double nlLH(Value ss)

See stats(...) of a data-set ds; for N data, {x_i}, nlLH = N.log A + (1/A) ∑ x_i.

Specified by:

nlLH in class Model

random_x

public double random_x()

Return random double from this Model, that is A*times;log(x), where x is uniform in [0,1).

Overrides:

random_x in class Continuous.M