| Modifier and Type | Class and Description |
|---|---|
class |
Direction.Uniform.M
Mdl should be sufficient for many purposes, but here is
M, the class of fully parameterised Uniform Direction Models. |
Direction.UniformR_D.Forest, R_D.ForestSearch, R_D.Independent, R_D.NrmDir, R_D.TransformUPModel.EstFunction.Native.WithInverseFunction.Cts2Cts, Function.Cts2Cts2Cts, Function.CtsD2CtsD, Function.HasInverse, Function.Native, Function.Native2, Function.Native3Value.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 |
|---|---|
int |
D
The dimension of RD; see
D(). |
Direction.Uniform.M |
Mdl
The (trivially) fully parameterised
Uniform Model of Directions.
|
| Constructor and Description |
|---|
Uniform(Value D)
Given dimension, D, construct a Uniform Direction UPModel.
|
| Modifier and Type | Method and Description |
|---|---|
int |
D()
The dimension of RD; return
D. |
Estimator |
estimator(Value t)
The trivial Estimator that is a Uniform Direction's.
|
Direction.Uniform.M |
sp2Model(double m1,
double m2,
Value t)
sp2Model(0, m2, ()) returns a
M Model. |
Value |
stats(boolean add,
Value ss0,
Value ss1)
Combine sufficient statisticses 'ss0' and 'ss1' additively
(add=true), or remove ss1 from ss0 (add=false).
|
Value |
stats(Vector ds,
int lo,
int hi)
The default sufficient statistics
|
ds2L1stats, ds2NorL1stats, ds2Nstats, transformpublic final int D
D().public final Direction.Uniform.M Mdl
public Uniform(Value D)
public Direction.Uniform.M sp2Model(double m1, double m2, Value t)
M Model.public Value stats(Vector ds, int lo, int hi)
Direction.Uniform.M.nlLH(la.la.Value).
More on stats here.public Value stats(boolean add, Value ss0, Value ss1)
UPModelstats(ds,lo,hi).