public class LogStar0UPM extends Discretes
MML.logStar0
should be enough for most purposes,
but here are the classes, UnParameterised (LogStar0UPM) and fully
(trivially) parameterised
(M).Modifier and Type | Class and Description |
---|---|
class |
LogStar0UPM.M
Model
logStar0 should be enough for most purposes,
but here are the classes, fully (trivially) parameterised (M)
and UnParameterised (LogStar0UPM ). |
Discretes.Bounded, Discretes.Shifted, Discretes.Uniform
UPModel.Est, 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 |
---|---|
LogStar0UPM.M |
Mdl
Note,
logStar0 is Mdl. |
Constructor and Description |
---|
LogStar0UPM(Value dp) |
Modifier and Type | Method and Description |
---|---|
Estimator |
estimator(Value t)
Return the "trivial" Estimator of
logStar0 . |
LogStar0UPM.M |
sp2Model(double msg1,
double msg2,
Value sp)
Return
logStar0 essentially, with msg2 set. |
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)
Return
|
java.lang.String |
toString()
Return a String representation of 'this' UnParameterised Model,
including its problem-
defining parameters. |
public final LogStar0UPM.M Mdl
logStar0
is Mdl.public LogStar0UPM(Value dp)
public Vector stats(Vector ds, int lo, int hi)
here
.public Vector stats(boolean add, Value ss0, Value ss1)
UPModel
stats(ds,lo,hi)
.public LogStar0UPM.M sp2Model(double msg1, double msg2, Value sp)
logStar0
essentially, with msg2 set.
Note that msg1 = 0 and sp = triv.