mml

Class Graphs.Skewed

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Graphs

mml.Graphs.Skewed

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Graphs

public static class Graphs.Skewed
extends Graphs

An UnParameterised Model of Graphs where the degree distribution is skewed, few Vertices having high degree and many having low degree. It is an attempt at something like (or including) a scale free, preferential attachment Model of Graphs. The fully parameterised Model is Graphs.Skewed.M. For similar Models of Graphs, I can think of plausible ways to calculate nlPr(G) (as here), and ways to to generate random Graphs, but not to do both in ways that exactly correspond.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Graphs.Skewed.M The fully parameterised Model of Skewed 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

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
Skewed(Value dp) Problem definition parameters dp = ⟨Graphs.gType, Graphs.upmV⟩.

Method Summary

Modifier and Type	Method and Description
UPModel.Est	estimator(Value ps) Only Graphs.M.mdlV is actually estimated.
Graphs.Skewed.M	sp2Model(double msg1, double msg2, Value sp) Return a fully parameterised Graphs.Skewed.M.
Vector	stats(boolean add, Value ss0, Value ss1) Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false).
Vector	stats(Vector ds, int lo, int hi) Sufficient statistics are elements [lo, hi) of the data-set 'ds' itself.

Methods inherited from class mml.Graphs

ds2mdlV, gType, 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

Skewed

public Skewed(Value dp)

Problem definition parameters dp = ⟨Graphs.gType, Graphs.upmV⟩.

Method Detail

stats

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

Sufficient statistics are elements [lo, hi) of the data-set 'ds' itself.

Overrides:

stats in class Graphs

stats

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

Description copied from class: UPModel

Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false). Also see stats(ds,lo,hi).

Overrides:

stats in class Graphs

estimator

public UPModel.Est estimator(Value ps)

Only Graphs.M.mdlV is actually estimated.

Overrides:

estimator in class UPModel

sp2Model

public Graphs.Skewed.M sp2Model(double msg1,
                                double msg2,
                                Value sp)

Return a fully parameterised Graphs.Skewed.M.

Specified by:

sp2Model in class UPModel