public class R_D.Transform extends R_D
R_D.Transform.M
.R_D.transform(f)
.Modifier and Type | Class and Description |
---|---|
class |
R_D.Transform.M
The parameterised R_D.Transform.M Model, the UnParameterised model
is
R_D.Transform . |
R_D.Forest, R_D.ForestSearch, R_D.Independent, R_D.NrmDir, R_D.Transform
UPModel.Est
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 |
---|---|
Function.CtsD2CtsD |
f
The Function, f:CtsD2CtsD,
RD→RD
doing the transforming of data.
|
Constructor and Description |
---|
Transform(Value f)
Problem defining parameter
'f' ' must be
a Function.CtsD2CtsD . |
Modifier and Type | Method and Description |
---|---|
int |
D()
The dimension D() of the data-space RD.
|
UPModel.Est |
estimator(Value ps)
Uses the enclosing R_D.this's estimator but
statistics take the transforming
function 'f ' into account. |
R_D.Transform.M |
sp2Model(double msg1,
double msg2,
Value sp)
Return a fully parameterised
R_D.Transform.M . |
Value |
stats(boolean add,
Value ss0,
Value ss1)
Combine
statistics ss0 and ss1 as per
the enclosing R_D.this. |
Value |
stats(Vector ds,
int lo,
int hi)
The enclosing R_D.this's stats(ds.map(
f ))
but on a transformed data-set, ds.map(f). |
java.lang.String |
toString()
Return a String representation of 'this' UnParameterised Model,
including its problem-
defining parameters. |
ds2L1stats, ds2NorL1stats, ds2Nstats, transform
public final Function.CtsD2CtsD f
public Transform(Value f)
'f'
' must be
a Function.CtsD2CtsD
.public R_D.Transform.M sp2Model(double msg1, double msg2, Value sp)
R_D.Transform.M
.public Value stats(Vector ds, int lo, int hi)
f
))
but on a transformed data-set, ds.map(f).public Value stats(boolean add, Value ss0, Value ss1)
statistics
ss0 and ss1 as per
the enclosing R_D.this.public java.lang.String toString()
UPModel
defining
parameters.public UPModel.Est estimator(Value ps)
statistics
take the transforming
function 'f
' into account.