public class Mixture extends UPModel
Model
; in this case, the
problem-defining
parameter is a UPModel
,
upm
, and the statistical
-parameters
are the weights, plus the statParams, of the clusters — the classes
in the Snob sense of "class". Here, each component is the same kind of
Model — a fully parameterised upm-Model.Modifier and Type | Class and Description |
---|---|
class |
Mixture.Est
|
class |
Mixture.M
A fully parameterised (non-abstract) Mixture Model
with
statistical -parameters being the
weights and parameters of the classes (clusters, components). |
UPModel.Transform
Function.Native.WithInverse
Function.Cts2Cts, Function.Cts2Cts2Cts, Function.CtsD2CtsD, Function.HasInverse, Function.Native, Function.Native2, Function.Native3
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
Modifier and Type | Field and Description |
---|---|
UPModel |
upm
The
UPModel of a class- (component-) sub-Model,
UPModel.defnParams() . |
Modifier and Type | Method and Description |
---|---|
Estimator |
estimator(Value ps)
Return an
estimator for 'this' Mixture;
note, its parameter will be upm's parameter. |
Mixture.M |
sp2Model(double m1,
double m2,
Value wp)
sp2Model(msg1, msg2, (wts,sps)) where wts is the weights of the
classes (clusters) and sps is the statParams of the classes, to
be given to
upm . |
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)
Mixture sufficient statistics, ss = ds.[lo,hi) itself.
|
public final UPModel upm
UPModel
of a class- (component-) sub-Model,
UPModel.defnParams()
.public Mixture(UPModel upm)
public Mixture.M sp2Model(double m1, double m2, Value wp)
upm
. Note that an MML message starts
with the # of components, N, here N=|wts| but it must be encoded.public Vector stats(Vector ds, int lo, int hi)
here
].public Vector stats(boolean add, Value ss0, Value ss1)
UPModel
stats(ds,lo,hi)
.