Taylor expansion of the characteristic function #
This file provides the Taylor expansion of the characteristic function of a measure at 0.
Main statements #
taylorWithinEval_charFun_zero: If a finite measureμoverℝadmits a moment of ordern, then the Taylor expansion of its characteristic function at0at ordernis given byt ↦ ∑ k ∈ Finset.range (n + 1), (k ! : ℂ)⁻¹ * (t * I) ^ k * ∫ x, x ^ k ∂μ.
Tags #
characteristic function, Taylor expansion
theorem
MeasureTheory.contDiff_charFun
{E : Type u_1}
[NormedAddCommGroup E]
[InnerProductSpace ℝ E]
[MeasurableSpace E]
[BorelSpace E]
[SecondCountableTopology E]
{μ : Measure E}
[IsFiniteMeasure μ]
{n : ℕ}
(hint : MemLp id (↑n) μ)
:
The characteristic function of a finite measure with a moment of order n is C^n.
See contDiff_charFun' for the version proving C^∞ by assuming all moments exist.
theorem
MeasureTheory.contDiff_charFun'
{E : Type u_1}
[NormedAddCommGroup E]
[InnerProductSpace ℝ E]
[MeasurableSpace E]
[BorelSpace E]
[SecondCountableTopology E]
{μ : Measure E}
[IsFiniteMeasure μ]
{n : ℕ∞}
(hint : ∀ (k : ℕ), MemLp id (↑k) μ)
:
The characteristic function of a measure with all moments is C^∞. See contDiff_charFun
for the version proving only C^n by only assuming that the moment of order n exists.
theorem
MeasureTheory.continuous_charFun
{E : Type u_1}
[NormedAddCommGroup E]
[InnerProductSpace ℝ E]
[MeasurableSpace E]
[BorelSpace E]
[SecondCountableTopology E]
{μ : Measure E}
[IsFiniteMeasure μ]
:
Continuous (charFun μ)
theorem
MeasureTheory.iteratedFDeriv_charFun
{E : Type u_1}
[NormedAddCommGroup E]
[InnerProductSpace ℝ E]
[MeasurableSpace E]
[BorelSpace E]
[SecondCountableTopology E]
{μ : Measure E}
[IsFiniteMeasure μ]
{n : ℕ}
{t : E}
(hint : MemLp id (↑n) μ)
(x : Fin n → E)
:
theorem
MeasureTheory.taylorWithinEval_charFun_two_zero
{Ω : Type u_1}
{mΩ : MeasurableSpace Ω}
{P : Measure Ω}
[IsProbabilityMeasure P]
{X : Ω → ℝ}
(hX : AEMeasurable X P)
(hint : MemLp id 2 (Measure.map X P))
(t : ℝ)
:
theorem
MeasureTheory.taylorWithinEval_charFun_two_zero'
{Ω : Type u_1}
{mΩ : MeasurableSpace Ω}
{P : Measure Ω}
[IsProbabilityMeasure P]
{X : Ω → ℝ}
(hX : AEMeasurable X P)
(h0 : ∫ (x : Ω), X x ∂P = 0)
(h1 : ∫ (x : Ω), (X ^ 2) x ∂P = 1)
(t : ℝ)
: