Filtrations #
This file defines filtrations of a measurable space and σ-finite filtrations.
Main definitions #
MeasureTheory.Filtration
: a filtration on a measurable space. That is, a monotone sequence of sub-σ-algebras.MeasureTheory.SigmaFiniteFiltration
: a filtrationf
is σ-finite with respect to a measureμ
if for alli
,μ.trim (f.le i)
is σ-finite.MeasureTheory.Filtration.natural
: the smallest filtration that makes a process adapted. That notionadapted
is not defined yet in this file. SeeMeasureTheory.adapted
.
Main results #
MeasureTheory.Filtration.instCompleteLattice
: filtrations are a complete lattice.
Tags #
filtration, stochastic process
A Filtration
on a measurable space Ω
with σ-algebra m
is a monotone
sequence of sub-σ-algebras of m
.
- seq : ι → MeasurableSpace Ω
- mono' : Monotone ↑self
- le' : ∀ (i : ι), ↑self i ≤ m
Instances For
Equations
- MeasureTheory.instCoeFunFiltrationForallMeasurableSpace = { coe := fun (f : MeasureTheory.Filtration ι m) => ↑f }
The constant filtration which is equal to m
for all i : ι
.
Equations
- MeasureTheory.Filtration.const ι m' hm' = { seq := fun (x : ι) => m', mono' := ⋯, le' := ⋯ }
Instances For
Equations
- MeasureTheory.Filtration.instInhabited = { default := MeasureTheory.Filtration.const ι m ⋯ }
Equations
- MeasureTheory.Filtration.instLE = { le := fun (f g : MeasureTheory.Filtration ι m) => ∀ (i : ι), ↑f i ≤ ↑g i }
Equations
- MeasureTheory.Filtration.instBot = { bot := MeasureTheory.Filtration.const ι ⊥ ⋯ }
Equations
- MeasureTheory.Filtration.instTop = { top := MeasureTheory.Filtration.const ι m ⋯ }
Equations
- MeasureTheory.Filtration.instSup = { sup := fun (f g : MeasureTheory.Filtration ι m) => { seq := fun (i : ι) => ↑f i ⊔ ↑g i, mono' := ⋯, le' := ⋯ } }
Equations
- MeasureTheory.Filtration.instInf = { inf := fun (f g : MeasureTheory.Filtration ι m) => { seq := fun (i : ι) => ↑f i ⊓ ↑g i, mono' := ⋯, le' := ⋯ } }
Equations
- One or more equations did not get rendered due to their size.
Equations
- One or more equations did not get rendered due to their size.
Equations
- MeasureTheory.Filtration.instCompleteLattice = CompleteLattice.mk ⋯ ⋯ ⋯ ⋯ ⋯ ⋯
A measure is σ-finite with respect to filtration if it is σ-finite with respect to all the sub-σ-algebra of the filtration.
- SigmaFinite : ∀ (i : ι), MeasureTheory.SigmaFinite (μ.trim ⋯)
Instances
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Given an integrable function g
, the conditional expectations of g
with respect to a
filtration is uniformly integrable.
Given a sequence of measurable sets (sₙ)
, filtrationOfSet
is the smallest filtration
such that sₙ
is measurable with respect to the n
-th sub-σ-algebra in filtrationOfSet
.
Equations
- MeasureTheory.filtrationOfSet hsm = { seq := fun (i : ι) => MeasurableSpace.generateFrom {t : Set Ω | ∃ j ≤ i, s j = t}, mono' := ⋯, le' := ⋯ }
Instances For
Given a sequence of functions, the natural filtration is the smallest sequence of σ-algebras such that that sequence of functions is measurable with respect to the filtration.
Equations
- MeasureTheory.Filtration.natural u hum = { seq := fun (i : ι) => ⨆ (j : ι), ⨆ (_ : j ≤ i), MeasurableSpace.comap (u j) mβ, mono' := ⋯, le' := ⋯ }
Instances For
Given a process f
and a filtration ℱ
, if f
converges to some g
almost everywhere and
g
is ⨆ n, ℱ n
-measurable, then limitProcess f ℱ μ
chooses said g
, else it returns 0.
This definition is used to phrase the a.e. martingale convergence theorem
Submartingale.ae_tendsto_limitProcess
where an L¹-bounded submartingale f
adapted to ℱ
converges to limitProcess f ℱ μ
μ
-almost everywhere.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Alias of MeasureTheory.Filtration.memℒp_limitProcess_of_eLpNorm_bdd
.