Conditional Independence #
We define conditional independence of sets/σ-algebras/functions with respect to a σ-algebra.
Two σ-algebras m₁ and m₂ are conditionally independent given a third σ-algebra m' if for all
m₁-measurable sets t₁ and m₂-measurable sets t₂,
μ⟦t₁ ∩ t₂ | m'⟧ =ᵐ[μ] μ⟦t₁ | m'⟧ * μ⟦t₂ | m'⟧.
On standard Borel spaces, the conditional expectation with respect to m' defines a kernel
ProbabilityTheory.condExpKernel, and the definition above is equivalent to
∀ᵐ ω ∂μ, condExpKernel μ m' ω (t₁ ∩ t₂) = condExpKernel μ m' ω t₁ * condExpKernel μ m' ω t₂.
We use this property as the definition of conditional independence.
Main definitions #
We provide four definitions of conditional independence:
iCondIndepSets: conditional independence of a family of sets of setspi : ι → Set (Set Ω). This is meant to be used with π-systems.iCondIndep: conditional independence of a family of measurable space structuresm : ι → MeasurableSpace Ω,iCondIndepSet: conditional independence of a family of setss : ι → Set Ω,iCondIndepFun: conditional independence of a family of functions. For measurable spacesm : Π (i : ι), MeasurableSpace (β i), we consider functionsf : Π (i : ι), Ω → β i.
Additionally, we provide four corresponding statements for two measurable space structures (resp.
sets of sets, sets, functions) instead of a family. These properties are denoted by the same names
as for a family, but without the starting i, for example CondIndepFun is the version of
iCondIndepFun for two functions.
Main statements #
ProbabilityTheory.iCondIndepSets.iCondIndep: if π-systems are conditionally independent as sets of sets, then the measurable space structures they generate are conditionally independent.ProbabilityTheory.condIndepSets.condIndep: variant with two π-systems.
Implementation notes #
The definitions of conditional independence in this file are a particular case of independence with
respect to a kernel and a measure, as defined in the file Probability/Independence/Kernel.lean.
The kernel used is ProbabilityTheory.condExpKernel.
A family of sets of sets π : ι → Set (Set Ω) is conditionally independent given m' with
respect to a measure μ if for any finite set of indices s = {i_1, ..., i_n}, for any sets
f i_1 ∈ π i_1, ..., f i_n ∈ π i_n, then μ⟦⋂ i in s, f i | m'⟧ =ᵐ[μ] ∏ i ∈ s, μ⟦f i | m'⟧.
See ProbabilityTheory.iCondIndepSets_iff.
It will be used for families of pi_systems.
Equations
- ProbabilityTheory.iCondIndepSets m' hm' π μ = ProbabilityTheory.Kernel.iIndepSets π (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
Two sets of sets s₁, s₂ are conditionally independent given m' with respect to a measure
μ if for any sets t₁ ∈ s₁, t₂ ∈ s₂, then μ⟦t₁ ∩ t₂ | m'⟧ =ᵐ[μ] μ⟦t₁ | m'⟧ * μ⟦t₂ | m'⟧.
See ProbabilityTheory.condIndepSets_iff.
Equations
- ProbabilityTheory.CondIndepSets m' hm' s1 s2 μ = ProbabilityTheory.Kernel.IndepSets s1 s2 (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
A family of measurable space structures (i.e. of σ-algebras) is conditionally independent given
m' with respect to a measure μ (typically defined on a finer σ-algebra) if the family of sets of
measurable sets they define is independent. m : ι → MeasurableSpace Ω is conditionally independent
given m' with respect to measure μ if for any finite set of indices s = {i_1, ..., i_n}, for
any sets f i_1 ∈ m i_1, ..., f i_n ∈ m i_n, then
μ⟦⋂ i in s, f i | m'⟧ =ᵐ[μ] ∏ i ∈ s, μ⟦f i | m'⟧ .
See ProbabilityTheory.iCondIndep_iff.
Equations
- ProbabilityTheory.iCondIndep m' hm' m μ = ProbabilityTheory.Kernel.iIndep m (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
Two measurable space structures (or σ-algebras) m₁, m₂ are conditionally independent given
m' with respect to a measure μ (defined on a third σ-algebra) if for any sets
t₁ ∈ m₁, t₂ ∈ m₂, μ⟦t₁ ∩ t₂ | m'⟧ =ᵐ[μ] μ⟦t₁ | m'⟧ * μ⟦t₂ | m'⟧.
See ProbabilityTheory.condIndep_iff.
Equations
- ProbabilityTheory.CondIndep m' m₁ m₂ hm' μ = ProbabilityTheory.Kernel.Indep m₁ m₂ (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
A family of sets is conditionally independent if the family of measurable space structures they
generate is conditionally independent. For a set s, the generated measurable space has measurable
sets ∅, s, sᶜ, univ.
See ProbabilityTheory.iCondIndepSet_iff.
Equations
- ProbabilityTheory.iCondIndepSet m' hm' s μ = ProbabilityTheory.Kernel.iIndepSet s (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
Two sets are conditionally independent if the two measurable space structures they generate are
conditionally independent. For a set s, the generated measurable space structure has measurable
sets ∅, s, sᶜ, univ.
See ProbabilityTheory.condIndepSet_iff.
Equations
- ProbabilityTheory.CondIndepSet m' hm' s t μ = ProbabilityTheory.Kernel.IndepSet s t (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
A family of functions defined on the same space Ω and taking values in possibly different
spaces, each with a measurable space structure, is conditionally independent if the family of
measurable space structures they generate on Ω is conditionally independent. For a function g
with codomain having measurable space structure m, the generated measurable space structure is
m.comap g.
See ProbabilityTheory.iCondIndepFun_iff.
Equations
- ProbabilityTheory.iCondIndepFun m' hm' f μ = ProbabilityTheory.Kernel.iIndepFun f (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
Two functions are conditionally independent if the two measurable space structures they generate
are conditionally independent. For a function f with codomain having measurable space structure
m, the generated measurable space structure is m.comap f.
See ProbabilityTheory.condIndepFun_iff.
Equations
- ProbabilityTheory.CondIndepFun m' hm' f g μ = ProbabilityTheory.Kernel.IndepFun f g (ProbabilityTheory.condExpKernel μ m') (μ.trim hm')
Instances For
Deducing CondIndep from iCondIndep #
π-system lemma #
Conditional independence of measurable spaces is equivalent to conditional independence of generating π-systems.
Conditional independence of σ-algebras implies conditional independence of #
generating π-systems
Conditional independence of generating π-systems implies conditional independence of #
σ-algebras
Alias of ProbabilityTheory.iCondIndepSets.piiUnionInter_of_notMem.
The σ-algebras generated by conditionally independent pi-systems are conditionally independent.
Conditional independence of measurable sets #
Conditional independence of random variables #
Alias of ProbabilityTheory.condIndepFun_iff_condExp_inter_preimage_eq_mul.
Alias of ProbabilityTheory.iCondIndepFun_iff_condExp_inter_preimage_eq_mul.
If f is a family of mutually conditionally independent random variables
(iCondIndepFun m' hm' m f μ) and S, T are two disjoint finite index sets, then the tuple formed
by f i for i ∈ S is conditionally independent of the tuple (f i)_i for i ∈ T.
Alias of ProbabilityTheory.iCondIndepFun.condIndepFun_prodMk.
Alias of ProbabilityTheory.iCondIndepFun.condIndepFun_prodMk_prodMk.
Alias of ProbabilityTheory.iCondIndepFun.condIndepFun_finset_sum_of_notMem.
Alias of ProbabilityTheory.iCondIndepFun.condIndepFun_finset_prod_of_notMem.