mml

Class Graphs.GERadaptive

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Graphs

mml.Graphs.IndependentEdges

mml.Graphs.GERadaptive

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Graphs

public static class Graphs.GERadaptive
extends Graphs.IndependentEdges

Special case of the Graphs.IndependentEdges Model where upmE() is Adaptive over [0, 1]. Therefore, every possible Edge in a Graph has the same probability of existing, but that probability is expected to change from Graph to Graph, even in the one data-set. The fully parameterised model is Graphs.GERadaptive.M. Also see Graphs.GERfixed.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Graphs.GERadaptive.M The fully parameterised Gilbert, Erdos-Renyi Adaptive Model of Graphs.

Nested classes/interfaces inherited from class mml.Graphs

Graphs.GERadaptive, Graphs.GERfixed, Graphs.IndependentEdges, Graphs.Motifs, Graphs.Skewed

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 inherited from class mml.Graphs.IndependentEdges

upmE

Fields inherited from class mml.Graphs

gType, upmV

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
GERadaptive(Value dp) Problem defining parameters dp = ⟨gType, upmV(), [α0, α1]⟩.

Method Summary

Modifier and Type	Method and Description
Discretes.Bounded.M	ds2mdlE(Value ps, Vector ds) Estimate a Discretes.Bounded.M, of Edge existence (0/1, false/true) from 'ds', a data-set of Graphs.
UPModel.Est	estimator(Value ps) Graphs.IndependentEdges.estimator(la.la.Value)(pair(ps,triv)), the triv for Adaptive's estimator.
Graphs.GERadaptive.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.

Methods inherited from class mml.Graphs.IndependentEdges

upmE

Methods inherited from class mml.Graphs

ds2mdlV, gType, stats, stats, upmV, vStats

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

Constructor Detail

GERadaptive

public GERadaptive(Value dp)

Problem defining parameters dp = ⟨gType, upmV(), [α₀, α₁]⟩. Note, it is hard-wired that upmE() (for Edges) is the Adaptive Model over [0,1], and [α₀, α₁] are the "offsets" for it; this also controls Edge-density of random() Graphs.

Method Detail

ds2mdlE

public Discretes.Bounded.M ds2mdlE(Value ps,
                                   Vector ds)

Description copied from class: Graphs.IndependentEdges

Estimate a Discretes.Bounded.M, of Edge existence (0/1, false/true) from 'ds', a data-set of Graphs. Requires parameter 'ps' for upmE's estimator(ps). Also see Graphs.IndependentEdges.M.mdlE().

Specified by:

ds2mdlE in class Graphs.IndependentEdges

estimator

public UPModel.Est estimator(Value ps)

Graphs.IndependentEdges.estimator(la.la.Value)(pair(ps,triv)), the triv for Adaptive's estimator.

Overrides:

estimator in class Graphs.IndependentEdges

sp2Model

public Graphs.GERadaptive.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 Graphs.IndependentEdges