public static class HeavyTail.Over_x1 extends Continuous
HeavyTail.Over_x1.M
and
its pdf is specified by pdf_x(x)
.Modifier and Type | Class and Description |
---|---|
class |
HeavyTail.Over_x1.M
|
Continuous.Bounded, Continuous.Transform, Continuous.Uniform
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
Constructor and Description |
---|
Over_x1(Value t)
No non-trivial problem-defining parameters; t=triv.
|
Modifier and Type | Method and Description |
---|---|
HeavyTail.Over_x1.M |
sp2Model(double msg1,
double msg2,
Value sp)
Given two-part message lengths msg1 & msg2, and statistical
parameter sp, return a fully parameterised
M-Model . |
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)
Sufficient statistics, ss = stats(ds,lo,hi), of elements
[lo,hi) of a data-set ds; here ss = ds.[lo,hi).
|
transform
apply, defnParams, estimator, main, stats, stats, toString, transform
public Over_x1(Value t)
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 HeavyTail.Over_x1.M sp2Model(double msg1, double msg2, Value sp)
UPModel
M-Model
.
If 'this' UPModel produces a Model m, then
sp2Model(m.msg1(), m.msg2(), m.statParams())
must be equivalent to m. Also see apply(sp)
.sp2Model
in class Continuous