mml

Class Missing

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Missing

All Implemented Interfaces:

java.lang.Comparable<Value>

public class Missing
extends UPModel

The UnParameterised Missing Model of "missing data" – data that may be known (present) or may be missing (absent, unknown). The fully parameterised Model is Missing.M.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Missing.M The fully parameterised Model; Missing is the UnParameterised Model.

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
MultiState	presentUPM The UnParameterised 2-state Model of whether a data value is known (present, true) or missing (absent, false).
UPModel	valueUPM The UnParameterised Model of those data that are known (present).

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
Missing(Value dp) Problem definition parameter 'dp' sets valueUPM.

Method Summary

Modifier and Type	Method and Description
UPModel.Est	estimator(Value ps) Return an Estimator of a fully parameterised Missing.M-Model.
static Vector	maybe_J(Vector ds) For a Vector 'ds' of Value.Maybe, return a Vector of those 'v' that are present in ds.
static Vector	present(Vector ds) For a Vector 'ds' of Value.Maybe, return a Vector of Bool.
Missing.M	sp2Model(double msg1, double msg2, Value sp) Given first- and second-part message lengths, msg1 and msg2, and statistical parameter(s), sp, return a fully parameterised Missing.M-Model.
Value.Tuple	stats(boolean add, Value ss0, Value ss1) Use presentUPM.stats(...) and valueUPM.stats(...).
Value.Tuple	stats(Vector ds, int lo, int hi) Use presentUPM.stats(...) and valueUPM.stats(...) to calculate the sufficient statistics of ds[lo,hi).

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

presentUPM

public final MultiState presentUPM

The UnParameterised 2-state Model of whether a data value is known (present, true) or missing (absent, false). Also see Missing.M.presentMdl.

valueUPM

public final UPModel valueUPM

The UnParameterised Model of those data that are known (present). It is set by the constructor and can be any UPModel of the (present) data. Also see Missing.M.valueMdl.

Constructor Detail

Missing

public Missing(Value dp)

Problem definition parameter 'dp' sets valueUPM.

Method Detail

sp2Model

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

Given first- and second-part message lengths, msg1 and msg2, and statistical parameter(s), sp, return a fully parameterised Missing.M-Model.

Specified by:

sp2Model in class UPModel

present

public static Vector present(Vector ds)

For a Vector 'ds' of Value.Maybe, return a Vector of Bool. That is of ffalse for a missing value 'None', and ttrue for a 'Just v'.

maybe_J

public static Vector maybe_J(Vector ds)

For a Vector 'ds' of Value.Maybe, return a Vector of those 'v' that are present in ds. That is values 'Just v' that are not missing. In general the result is shorter than ds. Note, it would be rather nice to return a shadow Vector, the same length as 'ds', and set the weights of missing values to zero, but is it guaranteed that all stats() etc. avoid even looking at such (non-)values???

stats

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

Use presentUPM.stats(...) and valueUPM.stats(...) to calculate the sufficient statistics of ds[lo,hi). Also see M.stats(...).

Specified by:

stats in class UPModel

stats

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

Use presentUPM.stats(...) and valueUPM.stats(...). Combine statistics ss0 and ss1, either ss0 "+" ss1, or ss0 "-" ss1, depending on 'add' being true or false. Also see M.stats(...).

Specified by:

stats in class UPModel

estimator

public UPModel.Est estimator(Value ps)

Return an Estimator of a fully parameterised Missing.M-Model. Its parameter 'ps' is a pair, one for the estimators of presentUPM and one for valueUPM.

Overrides:

estimator in class UPModel