mml

Class Intervals.M

java.lang.Object

la.la.Value

mml.Model

mml.FunctionModel

mml.UPFunctionModel.M

mml.Intervals.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Intervals

public class Intervals.M
extends UPFunctionModel.M

A fully parameterised FunctionModel in which the data-space of the input datum, id, is cut into intervals, and for each interval there is a (conditional) Model of the output datum, od. The UnParameterised FunctionModel is here.

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

Modifier and Type	Field and Description
Vector	cutPts The N-1 ordered cut-points, N≥1, dividing the data-space of the input datum, id, into N intervals (buckets), {<cp0, [cp0,cp1), ..., ≥cpN-2}.
Model[]	mdls The N Models of the output datum, od, one for each interval of id, N≥1.

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) M's statistical parameters, sp = (cutPts,sps), where sps are the statistical parameters for instances of upm.

Method Summary

Modifier and Type	Method and Description
Model	condModel(Value id) Return mdls[interval(id)].
int	interval(Value id) Return 'i' where input datum 'id' falls into interval 'i', 0 ≤ i < N.
double	nlLH(Value ss) Assumes that statistics 'ss' are the data-set itself (actually sorted).

Methods inherited from class mml.UPFunctionModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.FunctionModel

asUPModel, condNl2Pr, condNlPr, condPr, nlPr, pr, random, random

Methods inherited from class mml.Model

asEstimator, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, 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

cutPts

public final Vector cutPts

The N-1 ordered cut-points, N≥1, dividing the data-space of the input datum, id, into N intervals (buckets), {<cp₀, [cp₀,cp₁), ..., ≥cp_N-2}. Also see mdls.

mdls

public final Model[] mdls

The N Models of the output datum, od, one for each interval of id, N≥1.

Constructor Detail

M

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

M's statistical parameters, sp = (cutPts,sps), where sps are the statistical parameters for instances of upm.

Method Detail

nlLH

public double nlLH(Value ss)

Assumes that statistics 'ss' are the data-set itself (actually sorted).

Specified by:

nlLH in class Model

interval

public int interval(Value id)

Return 'i' where input datum 'id' falls into interval 'i', 0 ≤ i < N.

condModel

public Model condModel(Value id)

Return mdls[interval(id)]. That is, return the Model of od conditional on id.

Specified by:

condModel in class FunctionModel