mml

Class Model.Transform

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Model.Transform

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Model

public class Model.Transform
extends UPModel

Transform (the data for) Model.this by Function f (which is the problem defining parameter). Function 'f' must be 1–to–1. This amounts to applying the inverse, f⁻¹, to the random variable modelled by the Model being transformed, e.g., log−1=exp. Model.Transform is an UnParameterised model and its (trivially) parameterised Model is Model.Transform.M. Note, there is a more specific Continuous.M.Transform for transforming Continuous.M Models, and similarly R_D.M.Transform.
Transformed random() depends on f having an inverse() implemented.
NB. The preferred way to create a transformed Model is with function transform(f).
Also see the related but different UPModel.Transform and UPModel.Transform.M.
— April 2020.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Model.Transform.M The fully parameterised transformed Model has a trivial statistical parameter, sp.

Nested classes/interfaces inherited from class mml.UPModel

UPModel.Est, UPModel.Transform

Nested classes/interfaces inherited from class la.la.Function.Native

Function.Native.WithInverse

Nested classes/interfaces inherited from class la.la.Function

Function.Cts2Cts, Function.Cts2Cts2Cts, Function.CtsD2CtsD, Function.HasInverse, Function.Native, Function.Native2, Function.Native3

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
Function	f 'f' the function doing the transforming (of data).
Model.Transform.M	Mdl The instance of M, 'Mdl'.

Fields inherited from class mml.UPModel

dp

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
Transform(Value f) Note, Function 'f' is the problem defining parameter.

Method Summary

Modifier and Type	Method and Description
Estimator	estimator(Value t) Trivial estimator, always "estimates" Mdl.
Model.Transform.M	sp2Model(double msg1, double msg2, Value sp) Given two-part message lengths msg1 & msg2, and statistical parameter sp, return a fully parameterised M-Model.
Value	stats(boolean add, Value ss0, Value ss1) Combine statistics 'ss0' and 'ss1' in the way that Model.this does.
Value	stats(Vector ds, int lo, int hi) The enclosing Model.this's stats(...) applied to the data-set transformed by map(f).

Methods inherited from class mml.UPModel

apply, defnParams, main, stats, stats, toString, transform

Methods inherited from class la.la.Function

bOp, fromBop, fromUop, type, uOp

Methods inherited from class la.la.Value

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

Methods inherited from class java.lang.Object

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

Field Detail

f

public final Function f

'f' the function doing the transforming (of data).

Mdl

public final Model.Transform.M Mdl

The instance of M, 'Mdl'. msg1=msg2=0.

Constructor Detail

Transform

public Transform(Value f)

Note, Function 'f' is the problem defining parameter.

Method Detail

stats

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

The enclosing Model.this's stats(...) applied to the data-set transformed by map(f).

Specified by:

stats in class UPModel

stats

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

Combine statistics 'ss0' and 'ss1' in the way that Model.this does.

Specified by:

stats in class UPModel

sp2Model

public Model.Transform.M sp2Model(double msg1,
                                  double msg2,
                                  Value sp)

Description copied from class: UPModel

Given two-part message lengths msg1 & msg2, and statistical parameter sp, return a fully parameterised M-Model. If 'this' UPModel produces a Model m, then sp2Model(m.msg1(), m.msg2(), m.statParams()) must be equivalent to m. Also see apply(sp).

Specified by:

sp2Model in class UPModel

estimator

public Estimator estimator(Value t)

Trivial estimator, always "estimates" Mdl.

Overrides:

estimator in class UPModel