la.bioinformatics

Class Alignment.UPSame.M

java.lang.Object

la.la.Value

mml.Model

mml.SeriesModel

mml.UPSeriesModel.M

mml.UPSeriesModel.Length.M

la.bioinformatics.Alignment.UPSame.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

Alignment.UPSame

public class Alignment.UPSame.M
extends UPSeriesModel.Length.M

The fully parameterised SeriesModel of Alignments. It is built from sm3, smE and x2y. The UnParameterised SeriesModel is Alignment.UPSame.

Nested Class Summary

Nested classes/interfaces inherited from class mml.SeriesModel

SeriesModel.Analysis

Nested classes/interfaces inherited from class mml.Model

Model.Defaults

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
UPSeriesModel.Length.M	sm3 sm3, the SeriesModel of (LEFT | RIGHT | BOTH)*.
SeriesModel	smE smE, the SeriesModel of elements.
FunctionModel	x2y x2y, the Function Model of l→r and r→l.

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) Statistical parameters, sp, are for (UPsm3, UPsmE, UPx2y).

Method Summary

Modifier and Type	Method and Description
SeriesModel.Analysis	analysis(Value.Scannable sv) Separate out match/indel, Left elements, and Right elements from sv, do analyses of each, combine results.
Model	lenMdl() sm3.lenMdl() provides the Model of lengths.
double	nlLH(Value ss) Given sufficient statistics, ss = stats(ds), of a data-set, ds, return the negative log LikeliHood, nlLH(ss), of ds.

Methods inherited from class mml.UPSeriesModel.Length.M

lenStats, nlPr, random

Methods inherited from class mml.UPSeriesModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.SeriesModel

asUPModel

Methods inherited from class mml.Model

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

sm3

public final UPSeriesModel.Length.M sm3

sm3, the SeriesModel of (LEFT | RIGHT | BOTH)^*.

smE

public final SeriesModel smE

smE, the SeriesModel of elements.

x2y

public final FunctionModel x2y

x2y, the Function Model of l→r and r→l.

Constructor Detail

M

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

Statistical parameters, sp, are for (UPsm3, UPsmE, UPx2y).

Method Detail

nlLH

public double nlLH(Value ss)

Description copied from class: Model

Given sufficient statistics, ss = stats(ds), of a data-set, ds, return the negative log LikeliHood, nlLH(ss), of ds. Make sure that nlLH(ss), ss = stats(ds,lo,hi), and any Estimator are consistent!

Specified by:

nlLH in class Model

lenMdl

public Model lenMdl()

sm3.lenMdl() provides the Model of lengths.

Specified by:

lenMdl in class UPSeriesModel.Length.M

analysis

public SeriesModel.Analysis analysis(Value.Scannable sv)

Separate out match/indel, Left elements, and Right elements from sv, do analyses of each, combine results.

Specified by:

analysis in class SeriesModel