Measure spaces
Given a measurable space α
, a measure on α
is a function that sends measurable sets to the
extended nonnegative reals that satisfies the following conditions:
μ ∅ = 0
;μ
is countably additive. This means that the measure of a countable union of pairwise disjoint sets is equal to the measure of the individual sets.
Every measure can be canonically extended to an outer measure, so that it assigns values to all subsets, not just the measurable subsets. On the other hand, a measure that is countably additive on measurable sets can be restricted to measurable sets to obtain a measure. In this file a measure is defined to be an outer measure that is countably additive on measurable sets, with the additional assumption that the outer measure is the canonical extension of the restricted measure.
Measures on α
form a complete lattice, and are closed under scalar multiplication with ennreal
.
We introduce the following typeclasses for measures:
probability_measure μ
:μ univ = 1
;finite_measure μ
:μ univ < ⊤
;sigma_finite μ
: there exists a countable collection of measurable sets that coveruniv
whereμ
is finite;locally_finite_measure μ
:∀ x, ∃ s ∈ 𝓝 x, μ s < ⊤
;has_no_atoms μ
:∀ x, μ {x} = 0
; possibly should be redefined as∀ s, 0 < μ s → ∃ t ⊆ s, 0 < μ t ∧ μ t < μ s
.
Given a measure, the null sets are the sets where μ s = 0
, where μ
denotes the corresponding
outer measure (so s
might not be measurable). We can then define the completion of μ
as the
measure on the least σ
-algebra that also contains all null sets, by defining the measure to be 0
on the null sets.
Main statements
completion
is the completion of a measure to all null measurable sets.measure.of_measurable
andouter_measure.to_measure
are two important ways to define a measure.
Implementation notes
Given μ : measure α
, μ s
is the value of the outer measure applied to s
.
This conveniently allows us to apply the measure to sets without proving that they are measurable.
We get countable subadditivity for all sets, but only countable additivity for measurable sets.
You often don't want to define a measure via its constructor. Two ways that are sometimes more convenient:
measure.of_measurable
is a way to define a measure by only giving its value on measurable sets and proving the properties (1) and (2) mentioned above.outer_measure.to_measure
is a way of obtaining a measure from an outer measure by showing that all measurable sets in the measurable space are Carathéodory measurable.
To prove that two measures are equal, there are multiple options:
ext
: two measures are equal if they are equal on all measurable sets.ext_of_generate_from_of_Union
: two measures are equal if they are equal on a π-system generating the measurable sets, if the π-system contains a spanning increasing sequence of sets where the measures take finite value (in particular the measures are σ-finite). This is a special case of the more generalext_of_generate_from_of_cover
ext_of_generate_finite
: two finite measures are equal if they are equal on a π-system generating the measurable sets. This is a special case ofext_of_generate_from_of_Union
usingC ∪ {univ}
, but is easier to work with.
A measure_space
is a class that is a measurable space with a canonical measure.
The measure is denoted volume
.
References
- https://en.wikipedia.org/wiki/Measure_(mathematics)
- https://en.wikipedia.org/wiki/Complete_measure
- https://en.wikipedia.org/wiki/Almost_everywhere
Tags
measure, almost everywhere, measure space, completion, null set, null measurable set
- to_outer_measure : measure_theory.outer_measure α
- m_Union : ∀ ⦃f : ℕ → set α⦄, (∀ (i : ℕ), is_measurable (f i)) → pairwise (disjoint on f) → (c.to_outer_measure.measure_of (⋃ (i : ℕ), f i) = ∑' (i : ℕ), c.to_outer_measure.measure_of (f i))
- trimmed : c.to_outer_measure.trim = c.to_outer_measure
A measure is defined to be an outer measure that is countably additive on measurable sets, with the additional assumption that the outer measure is the canonical extension of the restricted measure.
Measure projections for a measure space.
For measurable sets this returns the measure assigned by the measure_of
field in measure
.
But we can extend this to _all_ sets, but using the outer measure. This gives us monotonicity and
subadditivity for all sets.
Equations
- measure_theory.measure.has_coe_to_fun = {F := λ (_x : measure_theory.measure α), set α → ennreal, coe := λ (m : measure_theory.measure α), ⇑(m.to_outer_measure)}
General facts about measures
Obtain a measure by giving a countably additive function that sends ∅
to 0
.
Equations
- measure_theory.measure.of_measurable m m0 mU = {to_outer_measure := {measure_of := (measure_theory.induced_outer_measure m is_measurable.empty m0).measure_of, empty := _, mono := _, Union_nat := _}, m_Union := _, trimmed := _}
If s
is a countable set, then the measure of its preimage can be found as the sum of measures
of the fibers f ⁻¹' {y}
.
If s
is a finset
, then the measure of its preimage can be found as the sum of measures
of the fibers f ⁻¹' {y}
.
Pigeonhole principle for measure spaces: if ∑' i, μ (s i) > μ univ
, then
one of the intersections s i ∩ s j
is not empty.
Pigeonhole principle for measure spaces: if s
is a finset
and
∑ i in s, μ (t i) > μ univ
, then one of the intersections t i ∩ t j
is not empty.
Continuity from below: the measure of the union of a directed sequence of measurable sets is the supremum of the measures.
Continuity from above: the measure of the intersection of a decreasing sequence of measurable sets is the infimum of the measures.
Continuity from below: the measure of the union of an increasing sequence of measurable sets is the limit of the measures.
Continuity from above: the measure of the intersection of a decreasing sequence of measurable sets is the limit of the measures.
One direction of the Borel-Cantelli lemma: if (sᵢ) is a sequence of measurable sets such that ∑ μ sᵢ exists, then the limit superior of the sᵢ is a null set.
Obtain a measure by giving an outer measure where all sets in the σ-algebra are Carathéodory measurable.
Equations
- m.to_measure h = measure_theory.measure.of_measurable (λ (s : set α) (_x : is_measurable s), ⇑m s) _ _
The ennreal
-module of measures
Equations
- measure_theory.measure.has_zero = {zero := {to_outer_measure := 0, m_Union := _, trimmed := _}}
Equations
- measure_theory.measure.has_add = {add := λ (μ₁ μ₂ : measure_theory.measure α), {to_outer_measure := μ₁.to_outer_measure + μ₂.to_outer_measure, m_Union := _, trimmed := _}}
Equations
- measure_theory.measure.has_scalar = {smul := λ (c : ennreal) (μ : measure_theory.measure α), {to_outer_measure := c • μ.to_outer_measure, m_Union := _, trimmed := _}}
The complete lattice of measures
Equations
- measure_theory.measure.partial_order = {le := λ (m₁ m₂ : measure_theory.measure α), ∀ (s : set α), is_measurable s → ⇑m₁ s ≤ ⇑m₂ s, lt := preorder.lt._default (λ (m₁ m₂ : measure_theory.measure α), ∀ (s : set α), is_measurable s → ⇑m₁ s ≤ ⇑m₂ s), le_refl := _, le_trans := _, lt_iff_le_not_le := _, le_antisymm := _}
Equations
- measure_theory.measure.complete_lattice = {sup := complete_lattice.sup (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), le := complete_lattice.le (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), lt := complete_lattice.lt (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), le_refl := _, le_trans := _, lt_iff_le_not_le := _, le_antisymm := _, le_sup_left := _, le_sup_right := _, sup_le := _, inf := complete_lattice.inf (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), inf_le_left := _, inf_le_right := _, le_inf := _, top := complete_lattice.top (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), le_top := _, bot := 0, bot_le := _, Sup := complete_lattice.Sup (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), Inf := complete_lattice.Inf (complete_lattice_of_Inf (measure_theory.measure α) measure_theory.measure.complete_lattice._proof_1), le_Sup := _, Sup_le := _, Inf_le := _, le_Inf := _}
Pushforward and pullback
Lift a linear map between outer_measure
spaces such that for each measure μ
every measurable
set is caratheodory-measurable w.r.t. f μ
to a linear map between measure
spaces.
Equations
- measure_theory.measure.lift_linear f hf = {to_fun := λ (μ : measure_theory.measure α), (⇑f μ.to_outer_measure).to_measure _, map_add' := _, map_smul' := _}
The pushforward of a measure. It is defined to be 0
if f
is not a measurable function.
Equations
- measure_theory.measure.map f = dite (measurable f) (λ (hf : measurable f), measure_theory.measure.lift_linear (measure_theory.outer_measure.map f) _) (λ (hf : ¬measurable f), 0)
Pullback of a measure
. If f
sends each measurable
set to a measurable
set, then for each
measurable set s
we have comap f μ s = μ (f '' s)
.
Equations
- measure_theory.measure.comap f = dite (function.injective f ∧ ∀ (s : set α), is_measurable s → is_measurable (f '' s)) (λ (hf : function.injective f ∧ ∀ (s : set α), is_measurable s → is_measurable (f '' s)), measure_theory.measure.lift_linear (measure_theory.outer_measure.comap f) _) (λ (hf : ¬(function.injective f ∧ ∀ (s : set α), is_measurable s → is_measurable (f '' s))), 0)
Restricting a measure
Restrict a measure μ
to a set s
as an ennreal
-linear map.
Restrict a measure μ
to a set s
.
Equations
- μ.restrict s = ⇑(measure_theory.measure.restrictₗ s) μ
Restriction of a measure to a subset is monotone both in set and in measure.
If two measures agree on all measurable subsets of s
and t
, then they agree on all
measurable subsets of s ∪ t
.
Extensionality results
Two measures are equal if they have equal restrictions on a spanning collection of sets
(formulated using Union
).
Two measures are equal if they have equal restrictions on a spanning collection of sets
(formulated using bUnion
).
Two measures are equal if they have equal restrictions on a spanning collection of sets
(formulated using sUnion
).
Two measures are equal if they are equal on the π-system generating the σ-algebra,
and they are both finite on a increasing spanning sequence of sets in the π-system.
This lemma is formulated using sUnion
.
Two measures are equal if they are equal on the π-system generating the σ-algebra,
and they are both finite on a increasing spanning sequence of sets in the π-system.
This lemma is formulated using Union
.
The dirac measure.
Equations
Sum of an indexed family of measures.
Equations
- measure_theory.measure.sum f = (measure_theory.outer_measure.sum (λ (i : ι), (f i).to_outer_measure)).to_measure _
Counting measure on any measurable space.
count
measure evaluates to infinity at infinite sets.
The almost everywhere filter
The “almost everywhere” filter of co-null sets.
The filter of sets s
such that sᶜ
has finite measure.
A version of the Borel-Cantelli lemma: if sᵢ is a sequence of measurable sets such that ∑ μ sᵢ exists, then for almost all x, x does not belong to almost all sᵢ.
If s ⊆ t
modulo a set of measure 0
, then μ s ≤ μ t
.
If two sets are equal modulo a set of measure zero, then μ s = μ t
.
A measure μ
is called a probability measure if μ univ = 1
.
A measure μ
is called finite if μ univ < ⊤
.
Measure μ
has no atoms if the measure of each singleton is zero.
NB: Wikipedia assumes that for any measurable set s
with positive μ
-measure,
there exists a measurable t ⊆ s
such that 0 < μ t < μ s
. While this implies μ {x} = 0
,
the converse is not true.
Instances
A measure is called finite at filter f
if it is finite at some set s ∈ f
.
Equivalently, it is eventually finite at s
in f.lift' powerset
.
- exists_finite_spanning_sets : ∃ (s : ℕ → set α), (∀ (i : ℕ), is_measurable (s i)) ∧ (∀ (i : ℕ), ⇑μ (s i) < ⊤) ∧ (⋃ (i : ℕ), s i) = set.univ
A measure μ
is called σ-finite if there is a countable collection of sets
{ A i | i ∈ ℕ }
such that μ (A i) < ⊤
and ⋃ i, A i = s
.
A noncomputable way to get a monotone collection of sets that span univ
and have finite
measure using classical.some
. This definition satisfies monotonicity in addition to all other
properties in sigma_finite
.
Equations
Every finite measure is σ-finite.
- finite_at_nhds : ∀ (x : α), μ.finite_at_filter (𝓝 x)
A measure is called locally finite if it is finite in some neighborhood of each point.
Two finite measures are equal if they are equal on the π-system generating the σ-algebra
(and univ
).
A measure is complete if every null set is also measurable.
A null set is a subset of a measurable set with measure 0
.
Since every measure is defined as a special case of an outer measure, we can more simply state
that a set s
is null if μ s = 0
.
Equations
- μ.is_complete = ∀ (s : set α), ⇑μ s = 0 → is_measurable s
Instances
A set is null measurable if it is the union of a null set and a measurable set.
Equations
- is_null_measurable μ s = ∃ (t z : set α), s = t ∪ z ∧ is_measurable t ∧ ⇑μ z = 0
The measurable space of all null measurable sets.
Equations
- null_measurable μ = {is_measurable' := is_null_measurable μ, is_measurable_empty := _, is_measurable_compl := _, is_measurable_Union := _}
Given a measure we can complete it to a (complete) measure on all null measurable sets.
Equations
- completion μ = {to_outer_measure := μ.to_outer_measure, m_Union := _, trimmed := _}
- to_measurable_space : measurable_space α
- volume : measure_theory.measure α
A measure space is a measurable space equipped with a
measure, referred to as volume
.
Instances
The tactic exact volume
, to be used in optional (auto_param
) arguments.