Kernel associated with a conditional expectation #
We define condExpKernel μ m
, a kernel from Ω
to Ω
such that for all integrable functions f
,
μ[f | m] =ᵐ[μ] fun ω => ∫ y, f y ∂(condExpKernel μ m ω)
.
This kernel is defined if Ω
is a standard Borel space. In general, μ⟦s | m⟧
maps a measurable
set s
to a function Ω → ℝ≥0∞
, and for all s
that map is unique up to a μ
-null set. For all
a
, the map from sets to ℝ≥0∞
that we obtain that way verifies some of the properties of a
measure, but the fact that the μ
-null set depends on s
can prevent us from finding versions of
the conditional expectation that combine into a true measure. The standard Borel space assumption
on Ω
allows us to do so.
Main definitions #
condExpKernel μ m
: kernel such thatμ[f | m] =ᵐ[μ] fun ω => ∫ y, f y ∂(condExpKernel μ m ω)
.
Main statements #
condExp_ae_eq_integral_condExpKernel
:μ[f | m] =ᵐ[μ] fun ω => ∫ y, f y ∂(condExpKernel μ m ω)
.
Kernel associated with the conditional expectation with respect to a σ-algebra. It satisfies
μ[f | m] =ᵐ[μ] fun ω => ∫ y, f y ∂(condExpKernel μ m ω)
.
It is defined as the conditional distribution of the identity given the identity, where the second
identity is understood as a map from Ω
with the σ-algebra mΩ
to Ω
with σ-algebra m ⊓ mΩ
.
We use m ⊓ mΩ
instead of m
to ensure that it is a sub-σ-algebra of mΩ
. We then use
Kernel.comap
to get a kernel from m
to mΩ
instead of from m ⊓ mΩ
to mΩ
.
Equations
- ProbabilityTheory.condExpKernel μ m = if _h : Nonempty Ω then (ProbabilityTheory.condDistrib id id μ).comap id ⋯ else 0
Instances For
Alias of ProbabilityTheory.condExpKernel
.
Kernel associated with the conditional expectation with respect to a σ-algebra. It satisfies
μ[f | m] =ᵐ[μ] fun ω => ∫ y, f y ∂(condExpKernel μ m ω)
.
It is defined as the conditional distribution of the identity given the identity, where the second
identity is understood as a map from Ω
with the σ-algebra mΩ
to Ω
with σ-algebra m ⊓ mΩ
.
We use m ⊓ mΩ
instead of m
to ensure that it is a sub-σ-algebra of mΩ
. We then use
Kernel.comap
to get a kernel from m
to mΩ
instead of from m ⊓ mΩ
to mΩ
.
Instances For
Alias of ProbabilityTheory.condExpKernel_eq
.
Alias of ProbabilityTheory.condExpKernel_apply_eq_condDistrib
.
Alias of ProbabilityTheory.stronglyMeasurable_condExpKernel
.
Alias of MeasureTheory.AEStronglyMeasurable.integral_condExpKernel
.
Alias of ProbabilityTheory.aestronglyMeasurable_integral_condExpKernel
.
Alias of ProbabilityTheory.aestronglyMeasurable_integral_condExpKernel
.
Alias of MeasureTheory.Integrable.integral_norm_condExpKernel
.
Alias of MeasureTheory.Integrable.norm_integral_condExpKernel
.
Alias of ProbabilityTheory.condExpKernel_ae_eq_trim_condExp
.
Alias of ProbabilityTheory.condExp_ae_eq_integral_condExpKernel'
.
The conditional expectation of f
with respect to a σ-algebra m
is almost everywhere equal to
the integral ∫ y, f y ∂(condExpKernel μ m ω)
.
Alias of ProbabilityTheory.condExp_ae_eq_integral_condExpKernel
.
The conditional expectation of f
with respect to a σ-algebra m
is almost everywhere equal to
the integral ∫ y, f y ∂(condExpKernel μ m ω)
.
Relation between conditional expectation, conditional kernel and the conditional measure. #
Alias of ProbabilityTheory.condExp_set_generateFrom_singleton
.
Alias of ProbabilityTheory.condExpKernel_singleton_ae_eq_cond
.