Measurable spaces and measurable functions #
This file provides properties of measurable spaces and the functions and isomorphisms between them.
The definition of a measurable space is in Mathlib/MeasureTheory/MeasurableSpace/Defs.lean
.
A measurable space is a set equipped with a σ-algebra, a collection of subsets closed under complementation and countable union. A function between measurable spaces is measurable if the preimage of each measurable subset is measurable.
σ-algebras on a fixed set α
form a complete lattice. Here we order
σ-algebras by writing m₁ ≤ m₂
if every set which is m₁
-measurable is
also m₂
-measurable (that is, m₁
is a subset of m₂
). In particular, any
collection of subsets of α
generates a smallest σ-algebra which
contains all of them. A function f : α → β
induces a Galois connection
between the lattices of σ-algebras on α
and β
.
We say that a filter f
is measurably generated if every set s ∈ f
includes a measurable
set t ∈ f
. This property is useful, e.g., to extract a measurable witness of Filter.Eventually
.
Implementation notes #
Measurability of a function f : α → β
between measurable spaces is
defined in terms of the Galois connection induced by f.
References #
- https://en.wikipedia.org/wiki/Measurable_space
- https://en.wikipedia.org/wiki/Sigma-algebra
- https://en.wikipedia.org/wiki/Dynkin_system
Tags #
measurable space, σ-algebra, measurable function, dynkin system, π-λ theorem, π-system
The forward image of a measurable space under a function. map f m
contains the sets
s : Set β
whose preimage under f
is measurable.
Equations
- MeasurableSpace.map f m = { MeasurableSet' := fun (s : Set β) => MeasurableSet (f ⁻¹' s), measurableSet_empty := ⋯, measurableSet_compl := ⋯, measurableSet_iUnion := ⋯ }
Instances For
The reverse image of a measurable space under a function. comap f m
contains the sets
s : Set α
such that s
is the f
-preimage of a measurable set in β
.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Alias of the forward direction of measurable_iff_le_map
.
Alias of the reverse direction of measurable_iff_le_map
.
Alias of the reverse direction of measurable_iff_comap_le
.
Alias of the forward direction of measurable_iff_comap_le
.
A version of measurable_const
that assumes f x = f y
for all x, y
. This version works
for functions between empty types.
This is slightly different from Measurable.piecewise
. It can be used to show
Measurable (ite (x=0) 0 1)
by
exact Measurable.ite (measurableSet_singleton 0) measurable_const measurable_const
,
but replacing Measurable.ite
by Measurable.piecewise
in that example proof does not work.
The measurability of a set A
is equivalent to the measurability of the indicator function
which takes a constant value b ≠ 0
on a set A
and 0
elsewhere.
If a function coincides with a measurable function outside of a countable set, it is measurable.
Equations
- ULift.instMeasurableSpace = MeasurableSpace.map ULift.up inst
Equations
- Quot.instMeasurableSpace = MeasurableSpace.map (Quot.mk r) m
Equations
- Quotient.instMeasurableSpace = MeasurableSpace.map Quotient.mk'' m
Equations
- QuotientGroup.measurableSpace S = Quotient.instMeasurableSpace
Equations
- QuotientAddGroup.measurableSpace S = Quotient.instMeasurableSpace
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Equations
- Subtype.instMeasurableSpace = MeasurableSpace.comap Subtype.val m
Equations
- ⋯ = ⋯
Alias of Measurable.subtype_coe
.
The measurable atom of x
is the intersection of all the measurable sets countaining x
.
It is measurable when the space is countable (or more generally when the measurable space is
countably generated).
Equations
- measurableAtom x = ⋂ (s : Set β), ⋂ (_ : x ∈ s), ⋂ (_ : MeasurableSet s), s
Instances For
A MeasurableSpace
structure on the product of two measurable spaces.
Equations
- m₁.prod m₂ = MeasurableSpace.comap Prod.fst m₁ ⊔ MeasurableSpace.comap Prod.snd m₂
Instances For
Equations
- Prod.instMeasurableSpace = m₁.prod m₂
Equations
- ⋯ = ⋯
A piecewise function on countably many pieces is measurable if all the data is measurable.
Let t i
be a countable covering of a set T
by measurable sets. Let f i : t i → β
be a
family of functions that agree on the intersections t i ∩ t j
. Then the function
Set.iUnionLift t f _ _ : T → β
, defined as f i ⟨x, hx⟩
for hx : x ∈ t i
, is measurable.
Let t i
be a countable covering of α
by measurable sets. Let f i : t i → β
be a family of
functions that agree on the intersections t i ∩ t j
. Then the function Set.liftCover t f _ _
,
defined as f i ⟨x, hx⟩
for hx : x ∈ t i
, is measurable.
Let t i
be a nonempty countable family of measurable sets in α
. Let g i : α → β
be a
family of measurable functions such that g i
agrees with g j
on t i ∩ t j
. Then there exists
a measurable function f : α → β
that agrees with each g i
on t i
.
We only need the assumption [Nonempty ι]
to prove [Nonempty (α → β)]
.
Equations
- MeasurableSpace.pi = ⨆ (a : δ), MeasurableSpace.comap (fun (b : (a : δ) → π a) => b a) (m a)
The function (f, x) ↦ update f a x : (Π a, π a) × π a → Π a, π a
is measurable.
The function update f a : π a → Π a, π a
is always measurable.
This doesn't require f
to be measurable.
This should not be confused with the statement that update f a x
is measurable.
Equations
- ⋯ = ⋯
Equations
- TProd.instMeasurableSpace π [] = PUnit.instMeasurableSpace
- TProd.instMeasurableSpace π (head :: is) = Prod.instMeasurableSpace
Equations
- Sum.instMeasurableSpace = MeasurableSpace.map Sum.inl m₁ ⊓ MeasurableSpace.map Sum.inr m₂
Alias of the reverse direction of measurableSet_inl_image
.
Alias of the reverse direction of measurableSet_inr_image
.
Equations
- Sigma.instMeasurableSpace = ⨅ (a : α), MeasurableSpace.map (Sigma.mk a) (m a)
Alias of the reverse direction of measurableSet_setOf
.
Alias of the reverse direction of measurable_mem
.
This instance is useful when talking about Bernoulli sequences of random variables or binomial random graphs.
Equations
- ⋯ = ⋯
The sigma-algebra generated by a single set s
is {∅, s, sᶜ, univ}
.
A filter f
is measurably generates if each s ∈ f
includes a measurable t ∈ f
.
- exists_measurable_subset : ∀ ⦃s : Set α⦄, s ∈ f → ∃ t ∈ f, MeasurableSet t ∧ t ⊆ s
Instances
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Alias of the reverse direction of Filter.principal_isMeasurablyGenerated_iff
.
Equations
- ⋯ = ⋯
The set of points for which a sequence of measurable functions converges to a given value is measurable.
We say that a collection of sets is countably spanning if a countable subset spans the
whole type. This is a useful condition in various parts of measure theory. For example, it is
a needed condition to show that the product of two collections generate the product sigma algebra,
see generateFrom_prod_eq
.
Equations
Instances For
Rectangles of countably spanning sets are countably spanning.
Typeclasses on Subtype MeasurableSet
#
Equations
- MeasurableSet.Subtype.instSingleton = { singleton := fun (a : α) => ⟨{a}, ⋯⟩ }
Equations
- ⋯ = ⋯
Equations
- MeasurableSet.Subtype.instTop = { top := ⟨Set.univ, ⋯⟩ }
Equations
- MeasurableSet.Subtype.instBooleanAlgebra = Function.Injective.booleanAlgebra (fun (a : Subtype MeasurableSet) => ↑a) ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯ ⋯