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 filtrationfis σ-finite with respect to a measureμif for alli,μ.trim (f.le i)is σ-finite.MeasureTheory.Filtration.natural: the smallest filtration that makes a process adapted. That notionadaptedis 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' := (_ : Monotone fun (x : ι) => m'), le' := (_ : ι → m' ≤ m) }
Instances For
Equations
- MeasureTheory.Filtration.instInhabitedFiltration = { default := MeasureTheory.Filtration.const ι m (_ : m ≤ m) }
Equations
- MeasureTheory.Filtration.instLEFiltration = { le := fun (f g : MeasureTheory.Filtration ι m) => ∀ (i : ι), ↑f i ≤ ↑g i }
Equations
- MeasureTheory.Filtration.instBotFiltration = { bot := MeasureTheory.Filtration.const ι ⊥ (_ : ⊥ ≤ m) }
Equations
- MeasureTheory.Filtration.instTopFiltration = { top := MeasureTheory.Filtration.const ι m (_ : m ≤ m) }
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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 (MeasureTheory.Measure.trim μ (_ : ↑f i ≤ m))
Instances
Equations
- (_ : MeasureTheory.SigmaFinite (MeasureTheory.Measure.trim μ (_ : ↑f i ≤ m))) = (_ : MeasureTheory.SigmaFinite (MeasureTheory.Measure.trim μ (_ : ↑f i ≤ m)))
Equations
- (_ : MeasureTheory.SigmaFiniteFiltration μ f) = (_ : MeasureTheory.SigmaFiniteFiltration μ f)
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.
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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.
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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.
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