mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : NormedSpace ℝ E
inst✝⁹ : MeasurableSpace E
inst✝⁸ : BorelSpace E
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : NormedSpace ℝ F
inst✝⁵ : MeasurableSpace F
inst✝⁴ : BorelSpace F
μ✝ : Measure E
inst✝³ : IsGaussian μ✝
inst✝² : SecondCountableTopology E
μ ν : Measure E
inst✝¹ : IsGaussian μ
inst✝ : IsGaussian ν
L : StrongDual ℝ E
⊢ AEStronglyMeasurable (fun x ↦ x) (Measure.map (⇑L) (μ ∗ ν))

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝¹¹ : NormedAddCommGroup E
inst✝¹⁰ : NormedSpace ℝ E
inst✝⁹ : MeasurableSpace E
inst✝⁸ : BorelSpace E
inst✝⁷ : NormedAddCommGroup F
inst✝⁶ : NormedSpace ℝ F
inst✝⁵ : MeasurableSpace F
inst✝⁴ : BorelSpace F
μ✝ : Measure E
inst✝³ : IsGaussian μ✝
inst✝² : SecondCountableTopology E
μ ν : Measure E
inst✝¹ : IsGaussian μ
inst✝ : IsGaussian ν
L : StrongDual ℝ E
this : ∫ (x : E), L x ∂μ ∗ ν = ∫ (x : ℝ), x ∂Measure.map (⇑L) μ ∗ Measure.map (⇑L) ν
⊢ AEMeasurable (⇑L) (μ ∗ ν)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
i j : ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ Measurable fun u ↦ ⟪(basisFun ι ℝ) i, u⟫

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
i j : ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ Measurable fun u ↦ ⟪(basisFun ι ℝ) j, u⟫

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
i j : ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ AEMeasurable (fun ω ↦ toLp 2 fun x ↦ X x ω) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ AEMeasurable (⇑L) (Measure.map (fun x ↦ x + c) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ AEMeasurable (fun x ↦ x + c) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ AEStronglyMeasurable (fun x ↦ ↑(L x)) (Measure.map (fun x ↦ x + c) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ AEStronglyMeasurable (⇑L) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
x y : EuclideanSpace ℝ ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ Measurable fun u ↦ ⟪x, u⟫

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
x y : EuclideanSpace ℝ ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ Measurable fun u ↦ ⟪y, u⟫

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
x y : EuclideanSpace ℝ ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ Measurable ?m.351

Tactic:
by fun_prop

Goal state after:
ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
x y : EuclideanSpace ℝ ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ Measurable ?m.351
Module: Mathlib.Probability.Moments.CovarianceBilin

Goal state before:
pp: ι : Type u_2
Ω : Type u_3
inst✝¹ : Fintype ι
mΩ : MeasurableSpace Ω
μ : Measure Ω
inst✝ : IsFiniteMeasure μ
X : ι → Ω → ℝ
hX : ∀ (i : ι), MemLp (X i) 2 μ
x y : EuclideanSpace ℝ ι
this : ∀ (i : ι), AEMeasurable (X i) μ
⊢ AEMeasurable (fun ω ↦ toLp 2 fun x ↦ X x ω) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ Integrable (⇑L) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
L : StrongDual ℝ E
hL_comp : (⇑L ∘ fun x ↦ x + c) = fun x ↦ L x + L c
⊢ Integrable (fun x ↦ L c) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
this : IsGaussian (Measure.map (fun x ↦ c + x) (Measure.map (fun x ↦ -x) μ))
⊢ Measurable fun x ↦ c + x

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
F : Type u_2
inst✝⁸ : NormedAddCommGroup E
inst✝⁷ : NormedSpace ℝ E
inst✝⁶ : MeasurableSpace E
inst✝⁵ : BorelSpace E
inst✝⁴ : NormedAddCommGroup F
inst✝³ : NormedSpace ℝ F
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
μ : Measure E
inst✝ : IsGaussian μ
c : E
this : IsGaussian (Measure.map (fun x ↦ c + x) (Measure.map (fun x ↦ -x) μ))
⊢ Measurable fun x ↦ -x

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ Measurable ⇑(ContinuousLinearMap.rotation (-(π / 4)))

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ Measurable fun p ↦ ‖p.1‖

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ Measurable fun p ↦ a

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ Measurable fun p ↦ b

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ Measurable fun p ↦ ‖p.2‖

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ (μ.prod μ) (⇑(ContinuousLinearMap.rotation (-(π / 4))) ⁻¹' {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖}) =
    (μ.prod μ) {p | ‖p.1 - p.2‖ / √2 ≤ a ∧ b < ‖p.1 + p.2‖ / √2}

Tactic:
congr 1

Goal state after:
case e_6
E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ ⇑(ContinuousLinearMap.rotation (-(π / 4))) ⁻¹' {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖} =
    {p | ‖p.1 - p.2‖ / √2 ≤ a ∧ b < ‖p.1 + p.2‖ / √2}
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝² : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : OpensMeasurableSpace E
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
x : E
hxL₁ : ↑↑(MemLp.toLp (fun x ↦ L₁ x) ⋯) x = L₁ x
hxL₂ : ↑↑(MemLp.toLp (fun x ↦ L₂ x) ⋯) x = L₂ x
⊢ ↑↑(MemLp.toLp ⇑L₂ ⋯) x * L₁ x = L₁ x * L₂ x

Tactic:
hxL₂,

Goal state after:
E : Type u_1
inst✝² : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : OpensMeasurableSpace E
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
x : E
hxL₁ : ↑↑(MemLp.toLp (fun x ↦ L₁ x) ⋯) x = L₁ x
hxL₂ : ↑↑(MemLp.toLp (fun x ↦ L₂ x) ⋯) x = L₂ x
⊢ L₂ x * L₁ x = L₁ x * L₂ x
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
inst✝ : SFinite μ
h : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
a b : ℝ
⊢ μ {x | ‖x‖ ≤ a} * μ {x | b < ‖x‖} ≤ μ {x | (b - a) / √2 < ‖x‖} ^ 2

Tactic:
by
  calc μ {x | ‖x‖ ≤ a} * μ {x | b < ‖x‖}
  _ = (μ.prod μ) ({x | ‖x‖ ≤ a} ×ˢ {y | b < ‖y‖}) := by rw [Measure.prod_prod]
    -- This is the measure of two bands in the plane (draw a picture!)
  _ = (μ.prod μ) {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖} := rfl
  _ = ((μ.prod μ).map (ContinuousLinearMap.rotation (-(π / 4)))) {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖} := by
    -- We can rotate the bands since `μ.prod μ` is invariant under rotation
    rw [h]
  _ = (μ.prod μ) {p | ‖p.1 - p.2‖ / √2 ≤ a ∧ b < ‖p.1 + p.2‖ / √2} := by
    rw [Measure.map_apply (by fun_prop)]
    swap
    · refine MeasurableSet.inter ?_ ?_
      · change MeasurableSet {p : E × E | ‖p.1‖ ≤ a}
        exact measurableSet_le (by fun_prop) (by fun_prop)
      · change MeasurableSet {p : E × E | b < ‖p.2‖}
        exact measurableSet_lt (by fun_prop) (by fun_prop)
    congr 1
    simp only [Set.preimage_ofPred_eq, ContinuousLinearMap.rotation_apply, Real.cos_neg,
      Real.cos_pi_div_four, Real.sin_neg, Real.sin_pi_div_four, neg_smul, neg_neg]
    have h_twos : ‖2⁻¹ * √2‖ = (√2)⁻¹ := by
      simp only [norm_mul, norm_inv, Real.norm_ofNat, Real.norm_eq_abs]
      rw [abs_of_nonneg (by positivity)]
      nth_rw 1 [← Real.sq_sqrt (by simp : (0 : ℝ) ≤ 2)]
      rw [pow_two, mul_inv, mul_assoc, inv_mul_cancel₀ (by positivity), mul_one]
    congr! with p
    · rw [← sub_eq_add_neg, ← smul_sub, norm_smul, div_eq_inv_mul, div_eq_inv_mul, h_twos]
    · rw [← smul_add, norm_smul, div_eq_inv_mul, div_eq_inv_mul, h_twos]
  _ ≤ (μ.prod μ) {p | (b - a) / √2 < ‖p.1‖ ∧ (b - a) / √2 < ‖p.2‖} := by
    -- The rotated bands are contained in quadrants.
    refine measure_mono fun p ↦ ?_
    simp only [Set.mem_ofPred_eq, and_imp]
    intro hp1 hp2
    suffices (b - a) / √2 < min ‖p.1‖ ‖p.2‖ from lt_min_iff.mp this
    calc (b - a) / √2
    _ < (‖p.1 + p.2‖ - ‖p.1 - p.2‖) / 2 := by
      suffices b - a < ‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2 by
        calc (b - a) / √2 < (‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2) / √2 := by gcongr
        _ = (‖p.1 + p.2‖ - ‖p.1 - p.2‖) / 2 := by
          field_simp; rw [Real.sq_sqrt (by positivity)]; ring
      calc b - a < ‖p.1 + p.2‖ / √2 - a := by gcongr
      _ ≤ ‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2 := by gcongr
    _ ≤ min ‖p.1‖ ‖p.2‖ := by
      have := norm_add_sub_norm_sub_le_two_mul_min p.1 p.2
      linarith
  _ = (μ.prod μ) ({x | (b - a) / √2 < ‖x‖} ×ˢ {y | (b - a) / √2 < ‖y‖}) := rfl
  _ ≤ μ {x | (b - a) / √2 < ‖x‖} ^ 2 := by rw [Measure.prod_prod, pow_two]

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
p : ℝ≥0∞
c : E := ∫ (x : E), x ∂μ
h_Lp : MemLp (fun x ↦ x - c) p μ
this : id = fun x ↦ x - c + c
hx : ¬c = 0
hp0 : p ≠ 0
hptop : p ≠ ∞
⊢ AEStronglyMeasurable (fun x ↦ c) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
p : ℝ≥0∞
c : E := ∫ (x : E), x ∂μ
h_Lp : MemLp (fun x ↦ x - c) p μ
this✝ : id = fun x ↦ x - c + c
hx : ¬c = 0
hp0 : p ≠ 0
hptop : p ≠ ∞
I : Integrable (fun x ↦ ‖x‖) μ
this : Integrable (fun x ↦ 2 ^ p.toReal * ‖x - c‖ ^ p.toReal) μ
⊢ AEStronglyMeasurable (fun x ↦ ‖c‖ ^ p.toReal) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
c : E := ∫ (x : E), x ∂μ
this✝¹ : id = fun x ↦ x - c + c
hx : ¬c = 0
I : Integrable (fun x ↦ ‖x‖) μ
y : E
p : ℝ≥0
h_Lp : MemLp (fun x ↦ x - c) (↑p) μ
hp0 : ↑p ≠ 0
this✝ : Integrable (fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) μ
h✝ : ‖y‖ ≤ ‖c‖ / 2
this : ‖c‖ ≤ ‖y‖ + ‖y - c‖
⊢ ‖c‖ ^ ↑p ≤ (2 * ‖y - c‖) ^ ↑p

Tactic:
gcongr
      linarith

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
a : ℝ
inst✝ : IsProbabilityMeasure μ
h_rot : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
ha_gt : 2⁻¹ < μ {x | ‖x‖ ≤ a}
c : ℝ≥0∞ := μ {x | ‖x‖ ≤ a}
hc_gt : 2⁻¹ < c
hc_pos : 0 < c
hc_lt_top : c < ∞
⊢ Measurable norm

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
a : ℝ
inst✝ : IsProbabilityMeasure μ
h_rot : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
ha_gt : 2⁻¹ < μ {x | ‖x‖ ≤ a}
c : ℝ≥0∞ := μ {x | ‖x‖ ≤ a}
hc_gt : 2⁻¹ < c
hc_pos : 0 < c
hc_lt_top : c < ∞
⊢ Measurable fun x ↦ a

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ Integrable (⇑L) (μ ∗ Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
x : E
⊢ Integrable (fun y ↦ L x) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
x : E
⊢ Integrable (⇑L) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ Integrable (⇑L) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ Integrable (fun x ↦ ∫ (y : E), L y ∂Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ AEMeasurable (⇑(ContinuousLinearEquiv.neg ℝ)) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ AEStronglyMeasurable (⇑L) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint : Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) (μ ∗ Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)
hC'_pos : 0 < C'
hC'_lt : C' < C
⊢ AEStronglyMeasurable (fun x ↦ rexp (C * ‖x‖ ^ 2)) (μ ∗ Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint :
  (∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)) ∧
    Integrable (fun x ↦ ∫ (y : E), ‖rexp (C * ‖x + y‖ ^ 2)‖ ∂Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ) μ
hC'_pos : 0 < C'
hC'_lt : C' < C
hC : ∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (-id) μ)
y : E
hy : Integrable (fun y_1 ↦ rexp (C * ‖y + y_1‖ ^ 2)) (Measure.map (-id) μ)
⊢ AEStronglyMeasurable (fun y_1 ↦ rexp (C * ‖y + y_1‖ ^ 2)) (Measure.map (-id) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint :
  (∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)) ∧
    Integrable (fun x ↦ ∫ (y : E), ‖rexp (C * ‖x + y‖ ^ 2)‖ ∂Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ) μ
hC'_pos : 0 < C'
hC'_lt : C' < C
hC : ∀ᵐ (x : E) ∂μ, Integrable (fun y ↦ rexp (C * ‖x + y‖ ^ 2)) (Measure.map (-id) μ)
y : E
hy : Integrable (fun y_1 ↦ rexp (C * ‖y + y_1‖ ^ 2)) (Measure.map (-id) μ)
⊢ AEMeasurable (-id) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝⁴ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝³ : NormedSpace ℝ E
inst✝² : BorelSpace E
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
⊢ AEMeasurable (fun x ↦ x - ∫ (x : E), x ∂μ) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝⁴ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝³ : NormedSpace ℝ E
inst✝² : BorelSpace E
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L₁ L₂ : StrongDual ℝ E
⊢ AEStronglyMeasurable (fun x ↦ L₁ x * L₂ x) (Measure.map (fun x ↦ x - ∫ (x : E), x ∂μ) μ)

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝⁴ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝³ : NormedSpace ℝ E
inst✝² : BorelSpace E
inst✝¹ : CompleteSpace E
inst✝ : IsFiniteMeasure μ
h : MemLp id 2 μ
L : StrongDual ℝ E
⊢ AEMeasurable (⇑L) μ

Tactic:
by fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
inst✝¹ : SecondCountableTopology E
μ : Measure E
inst✝ : IsGaussian μ
C C' : ℝ
hint : Integrable (fun x ↦ rexp (C * ‖x‖ ^ 2)) (μ ∗ Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ)
hC'_pos : 0 < C'
hC'_lt : C' < C
h_int : ∀ᵐ (y : E) ∂μ, Integrable (fun x ↦ rexp (C * ‖x - y‖ ^ 2)) μ
y : E
hy : Integrable (fun x ↦ rexp (C * ‖x - y‖ ^ 2)) μ
ε : ℝ := (C - C') / C'
hε : 0 < ε
this : ∀ (x : E), rexp (C' * ‖x‖ ^ 2) ≤ rexp (C / ε * ‖y‖ ^ 2) * rexp (C * ‖x - y‖ ^ 2)
⊢ AEStronglyMeasurable (fun x ↦ rexp (C' * ‖x‖ ^ 2)) μ

Tactic:
by fun_prop

Goal state after: