mml

Class Model.Defaults

java.lang.Object

la.la.Value

mml.Model

mml.Model.Defaults

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Model

public abstract static class Model.Defaults
extends Model

A subclass of Model that sets default methods stats(ds,lo,hi), stats(add,ss0,ss1) and nlLH(ss), even if they are slow. Only use (extend) Defaults if you cannot think of anything better, or you are very lazy.

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
Defaults(double msg1, double msg2, Value sp)

Method Summary

Modifier and Type	Method and Description
double	nlLH(Value ss) This default implementation assumes that statistics are the data themselves and uses sumNlPr but many Models can do better.
Value	stats(boolean add, Value ss0, Value ss1) statistics ss0 ± ss1, '+' if 'add' is true othewise '−'.
Value	stats(Vector ds, int lo, int hi) This default returns the data itself, ds.slice(lo,hi), as statistics but many Models can do much better.

Methods inherited from class mml.Model

asEstimator, asGiven, asGiven, asUPModel, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, nlPr, pr, random, random, randomSeries, statParams, stats, stats, sumNlPr, toString, 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

Defaults

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

Method Detail

stats

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

This default returns the data itself, ds.slice(lo,hi), as statistics but many Models can do much better. Note that ss=stats(ds,lo,hi), stats(add,ss0,ss1) and nlLH(ss)) must be consistent. Also see Model.stats(Vector,int,int).

Specified by:

stats in class Model

stats

public Value stats(boolean add,
                   Value ss0,
                   Value ss1)

statistics ss0 ± ss1, '+' if 'add' is true othewise '−'. This default implementation assumes statistics are the data themselves but many Models can do better.

Specified by:

stats in class Model

nlLH

public double nlLH(Value ss)

This default implementation assumes that statistics are the data themselves and uses sumNlPr but many Models can do better. Make sure that nlLH(ss), ss = stats(ds,lo,hi), and any Estimator are consistent!

Specified by:

nlLH in class Model