Conditional expectation in L1 #
This file contains two more steps of the construction of the conditional expectation, which is
completed in MeasureTheory.Function.ConditionalExpectation.Basic. See that file for a
description of the full process.
The contitional expectation of an L² function is defined in
MeasureTheory.Function.ConditionalExpectation.CondexpL2. In this file, we perform two steps.
- Show that the conditional expectation of the indicator of a measurable set with finite measure
is integrable and define a map
Set α → (E →L[ℝ] (α →₁[μ] E))which to a set associates a linear map. That linear map sendsx ∈ Eto the conditional expectation of the indicator of the set with valuex. - Extend that map to
condexpL1CLM : (α →₁[μ] E) →L[ℝ] (α →₁[μ] E). This is done using the same construction as the Bochner integral (see the fileMeasureTheory/Integral/SetToL1).
Main definitions #
condexpL1: Conditional expectation of a function as a linear map fromL1to itself.
Conditional expectation of an indicator as a continuous linear map. #
The goal of this section is to build
condexpInd (hm : m ≤ m0) (μ : Measure α) (s : Set s) : G →L[ℝ] α →₁[μ] G, which
takes x : G to the conditional expectation of the indicator of the set s with value x,
seen as an element of α →₁[μ] G.
Conditional expectation of the indicator of a measurable set with finite measure, as a function in L1.
Equations
- MeasureTheory.condexpIndL1Fin hm hs hμs x = MeasureTheory.Integrable.toL1 ↑↑(MeasureTheory.condexpIndSMul hm hs hμs x) ⋯
Instances For
Conditional expectation of the indicator of a set, as a function in L1. Its value for sets which are not both measurable and of finite measure is not used: we set it to 0.
Equations
- MeasureTheory.condexpIndL1 hm μ s x = if hs : MeasurableSet s ∧ μ s ≠ ⊤ then MeasureTheory.condexpIndL1Fin hm ⋯ ⋯ x else 0
Instances For
Conditional expectation of the indicator of a set, as a linear map from G to L1.
Equations
- MeasureTheory.condexpInd G hm μ s = { toFun := MeasureTheory.condexpIndL1 hm μ s, map_add' := ⋯, map_smul' := ⋯, cont := ⋯ }
Instances For
Alias of MeasureTheory.setIntegral_condexpInd.
Conditional expectation of a function as a linear map from α →₁[μ] F' to itself.
Equations
Instances For
Auxiliary lemma used in the proof of setIntegral_condexpL1CLM.
Alias of MeasureTheory.setIntegral_condexpL1CLM_of_measure_ne_top.
Auxiliary lemma used in the proof of setIntegral_condexpL1CLM.
The integral of the conditional expectation condexpL1CLM over an m-measurable set is equal
to the integral of f on that set. See also setIntegral_condexp, the similar statement for
condexp.
Alias of MeasureTheory.setIntegral_condexpL1CLM.
The integral of the conditional expectation condexpL1CLM over an m-measurable set is equal
to the integral of f on that set. See also setIntegral_condexp, the similar statement for
condexp.
Conditional expectation of a function, in L1. Its value is 0 if the function is not
integrable. The function-valued condexp should be used instead in most cases.
Equations
- MeasureTheory.condexpL1 hm μ f = MeasureTheory.setToFun μ (MeasureTheory.condexpInd F' hm μ) ⋯ f
Instances For
The integral of the conditional expectation condexpL1 over an m-measurable set is equal to
the integral of f on that set. See also setIntegral_condexp, the similar statement for
condexp.
Alias of MeasureTheory.setIntegral_condexpL1.
The integral of the conditional expectation condexpL1 over an m-measurable set is equal to
the integral of f on that set. See also setIntegral_condexp, the similar statement for
condexp.