Independence of sets of sets and measure spaces (σ-algebras) #
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- A family of sets of sets
π : ι → set (set Ω)is independent with respect to a measureμif for any finite set of indicess = {i_1, ..., i_n}, for any setsf i_1 ∈ π i_1, ..., f i_n ∈ π i_n,μ (⋂ i in s, f i) = ∏ i in s, μ (f i). It will be used for families of π-systems. - A family of measurable space structures (i.e. of σ-algebras) is independent 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. I.e.,m : ι → measurable_space Ωis independent with respect to a measureμif for any finite set of indicess = {i_1, ..., i_n}, for any setsf i_1 ∈ m i_1, ..., f i_n ∈ m i_n, thenμ (⋂ i in s, f i) = ∏ i in s, μ (f i). - Independence of sets (or events in probabilistic parlance) is defined as independence of the
measurable space structures they generate: a set
sgenerates the measurable space structure with measurable sets∅, s, sᶜ, univ. - Independence of functions (or random variables) is also defined as independence of the measurable
space structures they generate: a function
ffor which we have a measurable spacemon the codomain generatesmeasurable_space.comap f m.
Main statements #
Indep_sets.Indep: if π-systems are independent as sets of sets, then the measurable space structures they generate are independent.indep_sets.indep: variant with two π-systems.
Implementation notes #
We provide one main definition of independence:
Indep_sets: independence of a family of sets of setspi : ι → set (set Ω). Three other independence notions are defined usingIndep_sets:Indep: independence of a family of measurable space structuresm : ι → measurable_space Ω,Indep_set: independence of a family of setss : ι → set Ω,Indep_fun: independence of a family of functions. For measurable spacesm : Π (i : ι), measurable_space (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 a capital letter, for example indep_fun is the version of Indep_fun
for two functions.
The definition of independence for Indep_sets uses finite sets (finset). An alternative and
equivalent way of defining independence would have been to use countable sets.
TODO: prove that equivalence.
Most of the definitions and lemma in this file list all variables instead of using the variables
keyword at the beginning of a section, for example
lemma indep.symm {Ω} {m₁ m₂ : measurable_space Ω} [measurable_space Ω] {μ : measure Ω} ... .
This is intentional, to be able to control the order of the measurable_space variables. Indeed
when defining μ in the example above, the measurable space used is the last one defined, here
[measurable_space Ω], and not m₁ or m₂.
References #
- Williams, David. Probability with martingales. Cambridge university press, 1991. Part A, Chapter 4.
A family of sets of sets π : ι → set (set Ω) is independent 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) = ∏ i in s, μ (f i).
It will be used for families of pi_systems.
Two sets of sets s₁, s₂ are independent with respect to a measure μ if for any sets
t₁ ∈ p₁, t₂ ∈ s₂, then μ (t₁ ∩ t₂) = μ (t₁) * μ (t₂)
A family of measurable space structures (i.e. of σ-algebras) is independent 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 → measurable_space Ω is independent 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) = ∏ i in s, μ (f i).
Equations
- probability_theory.Indep m μ = probability_theory.Indep_sets (λ (x : ι), {s : set Ω | measurable_set s}) μ
Two measurable space structures (or σ-algebras) m₁, m₂ are independent with respect to a
measure μ (defined on a third σ-algebra) if for any sets t₁ ∈ m₁, t₂ ∈ m₂,
μ (t₁ ∩ t₂) = μ (t₁) * μ (t₂)
Equations
- probability_theory.indep m₁ m₂ μ = probability_theory.indep_sets {s : set Ω | measurable_set s} {s : set Ω | measurable_set s} μ
A family of sets is independent if the family of measurable space structures they generate is
independent. For a set s, the generated measurable space has measurable sets ∅, s, sᶜ, univ.
Equations
- probability_theory.Indep_set s μ = probability_theory.Indep (λ (i : ι), measurable_space.generate_from {s i}) μ
Two sets are independent if the two measurable space structures they generate are independent.
For a set s, the generated measurable space structure has measurable sets ∅, s, sᶜ, univ.
Equations
A family of functions defined on the same space Ω and taking values in possibly different
spaces, each with a measurable space structure, is independent if the family of measurable space
structures they generate on Ω is independent. For a function g with codomain having measurable
space structure m, the generated measurable space structure is measurable_space.comap g m.
Equations
- probability_theory.Indep_fun m f μ = probability_theory.Indep (λ (x : ι), measurable_space.comap (f x) (m x)) μ
Two functions are independent if the two measurable space structures they generate are
independent. For a function f with codomain having measurable space structure m, the generated
measurable space structure is measurable_space.comap f m.
Equations
- probability_theory.indep_fun f g μ = probability_theory.indep (measurable_space.comap f mβ) (measurable_space.comap g mγ) μ
Deducing indep from Indep #
π-system lemma #
Independence of measurable spaces is equivalent to independence of generating π-systems.
Independence of measurable space structures implies independence of generating π-systems #
Independence of generating π-systems implies independence of measurable space structures #
The measurable space structures generated by independent pi-systems are independent.
Independence of measurable sets #
We prove the following equivalences on indep_set, for measurable sets s, t.
indep_set s t μ ↔ μ (s ∩ t) = μ s * μ t,indep_set s t μ ↔ indep_sets {s} {t} μ.
Alias of the reverse direction of probability_theory.Indep_comap_mem_iff.
Independence of random variables #
If f is a family of mutually independent random variables (Indep_fun m f μ) and S, T are
two disjoint finite index sets, then the tuple formed by f i for i ∈ S is independent of the
tuple (f i)_i for i ∈ T.