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Found 84 declarations mentioning ProbabilityTheory.mgf.
- ProbabilityTheory.mgf 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} (X : Ω → ℝ) (μ : MeasureTheory.Measure Ω) (t : ℝ) : ℝ - ProbabilityTheory.mgf_nonneg 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} : 0 ≤ ProbabilityTheory.mgf X μ t - ProbabilityTheory.mgf_zero' 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} : ProbabilityTheory.mgf X μ 0 = μ.real Set.univ - ProbabilityTheory.mgf_const 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} (c : ℝ) [MeasureTheory.IsProbabilityMeasure μ] : ProbabilityTheory.mgf (fun x => c) μ t = Real.exp (t * c) - ProbabilityTheory.mgf_zero 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] : ProbabilityTheory.mgf X μ 0 = 1 - ProbabilityTheory.mgf_dirac' 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {t : ℝ} [MeasurableSingletonClass Ω] {ω : Ω} : ProbabilityTheory.mgf X (MeasureTheory.Measure.dirac ω) t = Real.exp (t * X ω) - ProbabilityTheory.mgf_zero_fun 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} : ProbabilityTheory.mgf 0 μ t = μ.real Set.univ - ProbabilityTheory.mgf_id_map 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (hX : AEMeasurable X μ) : ProbabilityTheory.mgf id (MeasureTheory.Measure.map X μ) = ProbabilityTheory.mgf X μ - ProbabilityTheory.mgf_neg 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} : ProbabilityTheory.mgf (-X) μ t = ProbabilityTheory.mgf X μ (-t) - ProbabilityTheory.mgf_zero_measure 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} : ProbabilityTheory.mgf X 0 = 0 - ProbabilityTheory.mgf_dirac 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {x : ℝ} (hX : ProbabilityTheory.HasLaw X (MeasureTheory.Measure.dirac x) μ) (t : ℝ) : ProbabilityTheory.mgf X μ t = Real.exp (x * t) - ProbabilityTheory.mgf_congr_identDistrib 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {Ω' : Type u_3} {mΩ' : MeasurableSpace Ω'} {μ' : MeasureTheory.Measure Ω'} {Y : Ω' → ℝ} (h : ProbabilityTheory.IdentDistrib X Y μ μ') : ProbabilityTheory.mgf X μ = ProbabilityTheory.mgf Y μ' - ProbabilityTheory.mgf_const' 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} (c : ℝ) : ProbabilityTheory.mgf (fun x => c) μ t = μ.real Set.univ * Real.exp (t * c) - ProbabilityTheory.mgf_congr 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} {Y : Ω → ℝ} (h : X =ᵐ[μ] Y) : ProbabilityTheory.mgf X μ t = ProbabilityTheory.mgf Y μ t - ProbabilityTheory.mgf_congr_of_identDistrib 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} (X : Ω → ℝ) {Ω' : Type u_3} {m' : MeasurableSpace Ω'} {μ' : MeasureTheory.Measure Ω'} (X' : Ω' → ℝ) (hident : ProbabilityTheory.IdentDistrib X X' μ μ') (t : ℝ) : ProbabilityTheory.mgf X μ t = ProbabilityTheory.mgf X' μ' t - ProbabilityTheory.mgf_const_mul 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (α : ℝ) : ProbabilityTheory.mgf (fun ω => α * X ω) μ t = ProbabilityTheory.mgf X μ (α * t) - ProbabilityTheory.mgf_smul_left 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (α : ℝ) : ProbabilityTheory.mgf (α • X) μ t = ProbabilityTheory.mgf X μ (α * t) - ProbabilityTheory.mgf_add_const 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (α : ℝ) : ProbabilityTheory.mgf (fun ω => X ω + α) μ t = ProbabilityTheory.mgf X μ t * Real.exp (t * α) - ProbabilityTheory.mgf_const_add 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (α : ℝ) : ProbabilityTheory.mgf (fun ω => α + X ω) μ t = Real.exp (t * α) * ProbabilityTheory.mgf X μ t - ProbabilityTheory.mgf_undef 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (hX : ¬MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : ProbabilityTheory.mgf X μ t = 0 - ProbabilityTheory.mgf_pos 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} [MeasureTheory.IsProbabilityMeasure μ] (h_int_X : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : 0 < ProbabilityTheory.mgf X μ t - ProbabilityTheory.iIndepFun.mgf_sum 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {ι : Type u_2} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} {X : ι → Ω → ℝ} (h_indep : ProbabilityTheory.iIndepFun X μ) (h_meas : ∀ (i : ι), Measurable (X i)) (s : Finset ι) : ProbabilityTheory.mgf (∑ i ∈ s, X i) μ t = ∏ i ∈ s, ProbabilityTheory.mgf (X i) μ t - ProbabilityTheory.iIndepFun.mgf_sum₀ 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {ι : Type u_2} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} {X : ι → Ω → ℝ} (h_indep : ProbabilityTheory.iIndepFun X μ) (h_meas : ∀ (i : ι), AEMeasurable (X i) μ) (s : Finset ι) : ProbabilityTheory.mgf (∑ i ∈ s, X i) μ t = ∏ i ∈ s, ProbabilityTheory.mgf (X i) μ t - ProbabilityTheory.exp_cgf 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} [hμ : NeZero μ] (hX : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : Real.exp (ProbabilityTheory.cgf X μ t) = ProbabilityTheory.mgf X μ t - ProbabilityTheory.mgf_pos_iff 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} [hμ : NeZero μ] : 0 < ProbabilityTheory.mgf X μ t ↔ MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ - ProbabilityTheory.mgf_smul_measure 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (c : ENNReal) : ProbabilityTheory.mgf X (c • μ) t = c.toReal * ProbabilityTheory.mgf X μ t - ProbabilityTheory.mgf_map 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {Ω' : Type u_3} {mΩ' : MeasurableSpace Ω'} {μ : MeasureTheory.Measure Ω'} {Y : Ω' → Ω} {X : Ω → ℝ} (hY : AEMeasurable Y μ) {t : ℝ} (hX : MeasureTheory.AEStronglyMeasurable (fun ω => Real.exp (t * X ω)) (MeasureTheory.Measure.map Y μ)) : ProbabilityTheory.mgf X (MeasureTheory.Measure.map Y μ) t = ProbabilityTheory.mgf (X ∘ Y) μ t - ProbabilityTheory.mgf_pos' 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (hμ : μ ≠ 0) (h_int_X : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : 0 < ProbabilityTheory.mgf X μ t - ProbabilityTheory.mgf_sum_measure 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {t : ℝ} {ι : Type u_3} {μ : ι → MeasureTheory.Measure Ω} (hμ : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) (MeasureTheory.Measure.sum μ)) : ProbabilityTheory.mgf X (MeasureTheory.Measure.sum μ) t = ∑' (i : ι), ProbabilityTheory.mgf X (μ i) t - ProbabilityTheory.mgf_anti_of_nonpos 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} {Y : Ω → ℝ} (hXY : X ≤ᵐ[μ] Y) (ht : t ≤ 0) (htX : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : ProbabilityTheory.mgf Y μ t ≤ ProbabilityTheory.mgf X μ t - ProbabilityTheory.mgf_mono_of_nonneg 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} {Y : Ω → ℝ} (hXY : X ≤ᵐ[μ] Y) (ht : 0 ≤ t) (htY : MeasureTheory.Integrable (fun ω => Real.exp (t * Y ω)) μ) : ProbabilityTheory.mgf X μ t ≤ ProbabilityTheory.mgf Y μ t - ProbabilityTheory.IndepFun.mgf_add' 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} {X Y : Ω → ℝ} (h_indep : ProbabilityTheory.IndepFun X Y μ) (hX : MeasureTheory.AEStronglyMeasurable X μ) (hY : MeasureTheory.AEStronglyMeasurable Y μ) : ProbabilityTheory.mgf (X + Y) μ t = ProbabilityTheory.mgf X μ t * ProbabilityTheory.mgf Y μ t - ProbabilityTheory.measure_ge_le_exp_mul_mgf 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} [MeasureTheory.IsFiniteMeasure μ] (ε : ℝ) (ht : 0 ≤ t) (h_int : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : μ.real {ω | ε ≤ X ω} ≤ Real.exp (-t * ε) * ProbabilityTheory.mgf X μ t - ProbabilityTheory.measure_le_le_exp_mul_mgf 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} [MeasureTheory.IsFiniteMeasure μ] (ε : ℝ) (ht : t ≤ 0) (h_int : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : μ.real {ω | X ω ≤ ε} ≤ Real.exp (-t * ε) * ProbabilityTheory.mgf X μ t - ProbabilityTheory.IndepFun.mgf_add 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {t : ℝ} {X Y : Ω → ℝ} (h_indep : ProbabilityTheory.IndepFun X Y μ) (hX : MeasureTheory.AEStronglyMeasurable (fun ω => Real.exp (t * X ω)) μ) (hY : MeasureTheory.AEStronglyMeasurable (fun ω => Real.exp (t * Y ω)) μ) : ProbabilityTheory.mgf (X + Y) μ t = ProbabilityTheory.mgf X μ t * ProbabilityTheory.mgf Y μ t - ProbabilityTheory.mgf_sum_of_identDistrib 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {ι : Type u_2} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : ι → Ω → ℝ} {s : Finset ι} {j : ι} (h_meas : ∀ (i : ι), Measurable (X i)) (h_indep : ProbabilityTheory.iIndepFun X μ) (hident : ∀ i ∈ s, ∀ j ∈ s, ProbabilityTheory.IdentDistrib (X i) (X j) μ μ) (hj : j ∈ s) (t : ℝ) : ProbabilityTheory.mgf (∑ i ∈ s, X i) μ t = ProbabilityTheory.mgf (X j) μ t ^ s.card - ProbabilityTheory.mgf_add_measure 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} {ν : MeasureTheory.Measure Ω} (hμ : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) (hν : MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) ν) : ProbabilityTheory.mgf X (μ + ν) t = ProbabilityTheory.mgf X μ t + ProbabilityTheory.mgf X ν t - ProbabilityTheory.mgf_sum_of_identDistrib₀ 📋 Mathlib.Probability.Moments.Basic
{Ω : Type u_1} {ι : Type u_2} {m : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : ι → Ω → ℝ} {s : Finset ι} {j : ι} (h_meas : ∀ (i : ι), AEMeasurable (X i) μ) (h_indep : ProbabilityTheory.iIndepFun X μ) (hident : ∀ i ∈ s, ∀ j ∈ s, ProbabilityTheory.IdentDistrib (X i) (X j) μ μ) (hj : j ∈ s) (t : ℝ) : ProbabilityTheory.mgf (∑ i ∈ s, X i) μ t = ProbabilityTheory.mgf (X j) μ t ^ s.card - ProbabilityTheory.complexMGF_ofReal 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (x : ℝ) : ProbabilityTheory.complexMGF X μ ↑x = ↑(ProbabilityTheory.mgf X μ x) - ProbabilityTheory.re_complexMGF_ofReal 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (x : ℝ) : (ProbabilityTheory.complexMGF X μ ↑x).re = ProbabilityTheory.mgf X μ x - ProbabilityTheory.re_complexMGF_ofReal' 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} : (fun x => (ProbabilityTheory.complexMGF X μ ↑x).re) = ProbabilityTheory.mgf X μ - ProbabilityTheory.norm_complexMGF_le_mgf 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {z : ℂ} : ‖ProbabilityTheory.complexMGF X μ z‖ ≤ ProbabilityTheory.mgf X μ z.re - ProbabilityTheory.integrableExpSet_eq_of_mgf 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {Ω' : Type u_2} {mΩ' : MeasurableSpace Ω'} {Y : Ω' → ℝ} {μ' : MeasureTheory.Measure Ω'} [MeasureTheory.IsProbabilityMeasure μ] (hXY : ProbabilityTheory.mgf X μ = ProbabilityTheory.mgf Y μ') : ProbabilityTheory.integrableExpSet X μ = ProbabilityTheory.integrableExpSet Y μ' - ProbabilityTheory.eqOn_complexMGF_of_mgf 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {Ω' : Type u_2} {mΩ' : MeasurableSpace Ω'} {Y : Ω' → ℝ} {μ' : MeasureTheory.Measure Ω'} [MeasureTheory.IsProbabilityMeasure μ] (hXY : ProbabilityTheory.mgf X μ = ProbabilityTheory.mgf Y μ') : Set.EqOn (ProbabilityTheory.complexMGF X μ) (ProbabilityTheory.complexMGF Y μ') {z | z.re ∈ interior (ProbabilityTheory.integrableExpSet X μ)} - ProbabilityTheory.integrableExpSet_eq_of_mgf' 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {Ω' : Type u_2} {mΩ' : MeasurableSpace Ω'} {Y : Ω' → ℝ} {μ' : MeasureTheory.Measure Ω'} (hXY : ProbabilityTheory.mgf X μ = ProbabilityTheory.mgf Y μ') (hμμ' : μ = 0 ↔ μ' = 0) : ProbabilityTheory.integrableExpSet X μ = ProbabilityTheory.integrableExpSet Y μ' - ProbabilityTheory.eqOn_complexMGF_of_mgf' 📋 Mathlib.Probability.Moments.ComplexMGF
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {Ω' : Type u_2} {mΩ' : MeasurableSpace Ω'} {Y : Ω' → ℝ} {μ' : MeasureTheory.Measure Ω'} (hXY : ProbabilityTheory.mgf X μ = ProbabilityTheory.mgf Y μ') (hμμ' : μ = 0 ↔ μ' = 0) : Set.EqOn (ProbabilityTheory.complexMGF X μ) (ProbabilityTheory.complexMGF Y μ') {z | z.re ∈ interior (ProbabilityTheory.integrableExpSet X μ)} - ProbabilityTheory.continuousOn_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} : ContinuousOn (ProbabilityTheory.mgf X μ) (interior (ProbabilityTheory.integrableExpSet X μ)) - ProbabilityTheory.analyticOnNhd_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} : AnalyticOnNhd ℝ (ProbabilityTheory.mgf X μ) (interior (ProbabilityTheory.integrableExpSet X μ)) - ProbabilityTheory.analyticOn_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} : AnalyticOn ℝ (ProbabilityTheory.mgf X μ) (interior (ProbabilityTheory.integrableExpSet X μ)) - ProbabilityTheory.continuous_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (h : ∀ (t : ℝ), MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) : Continuous (ProbabilityTheory.mgf X μ) - ProbabilityTheory.analyticAt_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (ht : t ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : AnalyticAt ℝ (ProbabilityTheory.mgf X μ) t - ProbabilityTheory.analyticOnNhd_iteratedDeriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (n : ℕ) : AnalyticOnNhd ℝ (iteratedDeriv n (ProbabilityTheory.mgf X μ)) (interior (ProbabilityTheory.integrableExpSet X μ)) - ProbabilityTheory.analyticOn_iteratedDeriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (n : ℕ) : AnalyticOn ℝ (iteratedDeriv n (ProbabilityTheory.mgf X μ)) (interior (ProbabilityTheory.integrableExpSet X μ)) - ProbabilityTheory.differentiableOn_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} : DifferentiableOn ℝ (ProbabilityTheory.mgf X μ) (interior (ProbabilityTheory.integrableExpSet X μ)) - ProbabilityTheory.analyticAt_iteratedDeriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {v : ℝ} (hv : v ∈ interior (ProbabilityTheory.integrableExpSet X μ)) (n : ℕ) : AnalyticAt ℝ (iteratedDeriv n (ProbabilityTheory.mgf X μ)) v - ProbabilityTheory.differentiableAt_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (ht : t ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : DifferentiableAt ℝ (ProbabilityTheory.mgf X μ) t - ProbabilityTheory.deriv_mgf_zero 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (h : 0 ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : deriv (ProbabilityTheory.mgf X μ) 0 = ∫ (x : Ω), X x ∂μ - ProbabilityTheory.deriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (h : t ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : deriv (ProbabilityTheory.mgf X μ) t = ∫ (x : Ω), (fun ω => X ω * Real.exp (t * X ω)) x ∂μ - ProbabilityTheory.differentiableAt_iteratedDeriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {v : ℝ} (hv : v ∈ interior (ProbabilityTheory.integrableExpSet X μ)) (n : ℕ) : DifferentiableAt ℝ (iteratedDeriv n (ProbabilityTheory.mgf X μ)) v - ProbabilityTheory.iteratedDeriv_mgf_zero 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} (h : 0 ∈ interior (ProbabilityTheory.integrableExpSet X μ)) (n : ℕ) : iteratedDeriv n (ProbabilityTheory.mgf X μ) 0 = ∫ (x : Ω), (X ^ n) x ∂μ - ProbabilityTheory.iteratedDeriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (ht : t ∈ interior (ProbabilityTheory.integrableExpSet X μ)) (n : ℕ) : iteratedDeriv n (ProbabilityTheory.mgf X μ) t = ∫ (x : Ω), (fun ω => X ω ^ n * Real.exp (t * X ω)) x ∂μ - ProbabilityTheory.deriv_cgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {v : ℝ} (h : v ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : deriv (ProbabilityTheory.cgf X μ) v = (∫ (x : Ω), (fun ω => X ω * Real.exp (v * X ω)) x ∂μ) / ProbabilityTheory.mgf X μ v - ProbabilityTheory.hasFPowerSeriesAt_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {v : ℝ} (hv : v ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : HasFPowerSeriesAt (ProbabilityTheory.mgf X μ) (FormalMultilinearSeries.ofScalars ℝ fun n => (∫ (x : Ω), (fun ω => X ω ^ n * Real.exp (v * X ω)) x ∂μ) / ↑n.factorial) v - ProbabilityTheory.iteratedDeriv_two_cgf_eq_integral 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {v : ℝ} (h : v ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : iteratedDeriv 2 (ProbabilityTheory.cgf X μ) v = (∫ (x : Ω), (fun ω => (X ω - deriv (ProbabilityTheory.cgf X μ) v) ^ 2 * Real.exp (v * X ω)) x ∂μ) / ProbabilityTheory.mgf X μ v - ProbabilityTheory.iteratedDeriv_two_cgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {v : ℝ} (h : v ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : iteratedDeriv 2 (ProbabilityTheory.cgf X μ) v = (∫ (x : Ω), (fun ω => X ω ^ 2 * Real.exp (v * X ω)) x ∂μ) / ProbabilityTheory.mgf X μ v - deriv (ProbabilityTheory.cgf X μ) v ^ 2 - ProbabilityTheory.hasDerivAt_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (h : t ∈ interior (ProbabilityTheory.integrableExpSet X μ)) : HasDerivAt (ProbabilityTheory.mgf X μ) (∫ (x : Ω), (fun ω => X ω * Real.exp (t * X ω)) x ∂μ) t - ProbabilityTheory.hasDerivAt_iteratedDeriv_mgf 📋 Mathlib.Probability.Moments.MGFAnalytic
{Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : MeasureTheory.Measure Ω} {t : ℝ} (ht : t ∈ interior (ProbabilityTheory.integrableExpSet X μ)) (n : ℕ) : HasDerivAt (iteratedDeriv n (ProbabilityTheory.mgf X μ)) (∫ (x : Ω), (fun ω => X ω ^ (n + 1) * Real.exp (t * X ω)) x ∂μ) t - ProbabilityTheory.mgf_fun_id_gaussianReal 📋 Mathlib.Probability.Distributions.Gaussian.Real
{μ : ℝ} {v : NNReal} : ProbabilityTheory.mgf (fun x => x) (ProbabilityTheory.gaussianReal μ v) = fun t => Real.exp (μ * t + ↑v * t ^ 2 / 2) - ProbabilityTheory.mgf_id_gaussianReal 📋 Mathlib.Probability.Distributions.Gaussian.Real
{μ : ℝ} {v : NNReal} : ProbabilityTheory.mgf id (ProbabilityTheory.gaussianReal μ v) = fun t => Real.exp (μ * t + ↑v * t ^ 2 / 2) - ProbabilityTheory.mgf_gaussianReal 📋 Mathlib.Probability.Distributions.Gaussian.Real
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {p : MeasureTheory.Measure Ω} {μ : ℝ} {v : NNReal} {X : Ω → ℝ} (hX : ProbabilityTheory.HasLaw X (ProbabilityTheory.gaussianReal μ v) p) (t : ℝ) : ProbabilityTheory.mgf X p t = Real.exp (μ * t + ↑v * t ^ 2 / 2) - ProbabilityTheory.tilted_mul_apply_mgf 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} [MeasureTheory.SFinite μ] (s : Set Ω) : (μ.tilted fun x => t * X x) s = ∫⁻ (a : Ω) in s, ENNReal.ofReal (Real.exp (t * X a) / ProbabilityTheory.mgf X μ t) ∂μ - ProbabilityTheory.tilted_mul_apply_mgf' 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} {s : Set Ω} (hs : MeasurableSet s) : (μ.tilted fun x => t * X x) s = ∫⁻ (a : Ω) in s, ENNReal.ofReal (Real.exp (t * X a) / ProbabilityTheory.mgf X μ t) ∂μ - ProbabilityTheory.tilted_mul_apply_eq_ofReal_integral_mgf 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} [MeasureTheory.SFinite μ] (s : Set Ω) : (μ.tilted fun x => t * X x) s = ENNReal.ofReal (∫ (a : Ω) in s, Real.exp (t * X a) / ProbabilityTheory.mgf X μ t ∂μ) - ProbabilityTheory.tilted_mul_apply_eq_ofReal_integral_mgf' 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} {s : Set Ω} (hs : MeasurableSet s) : (μ.tilted fun x => t * X x) s = ENNReal.ofReal (∫ (a : Ω) in s, Real.exp (t * X a) / ProbabilityTheory.mgf X μ t ∂μ) - ProbabilityTheory.integral_tilted_mul_eq_mgf 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} {E : Type u_2} [NormedAddCommGroup E] [NormedSpace ℝ E] (g : Ω → E) : (∫ (ω : Ω), g ω ∂μ.tilted fun x => t * X x) = ∫ (ω : Ω), (Real.exp (t * X ω) / ProbabilityTheory.mgf X μ t) • g ω ∂μ - ProbabilityTheory.setIntegral_tilted_mul_eq_mgf 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} {E : Type u_2} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasureTheory.SFinite μ] (g : Ω → E) (s : Set Ω) : (∫ (x : Ω) in s, g x ∂μ.tilted fun x => t * X x) = ∫ (x : Ω) in s, (Real.exp (t * X x) / ProbabilityTheory.mgf X μ t) • g x ∂μ - ProbabilityTheory.setIntegral_tilted_mul_eq_mgf' 📋 Mathlib.Probability.Moments.Tilted
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} {t : ℝ} {E : Type u_2} [NormedAddCommGroup E] [NormedSpace ℝ E] (g : Ω → E) {s : Set Ω} (hs : MeasurableSet s) : (∫ (x : Ω) in s, g x ∂μ.tilted fun x => t * X x) = ∫ (x : Ω) in s, (Real.exp (t * X x) / ProbabilityTheory.mgf X μ t) • g x ∂μ - ProbabilityTheory.HasSubgaussianMGF.mgf_le 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {X : Ω → ℝ} {c : NNReal} {μ : autoParam (MeasureTheory.Measure Ω) ProbabilityTheory.HasSubgaussianMGF._auto_1} (self : ProbabilityTheory.HasSubgaussianMGF X c μ) (t : ℝ) : ProbabilityTheory.mgf X μ t ≤ Real.exp (↑c * t ^ 2 / 2) - ProbabilityTheory.HasSubgaussianMGF.mk 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {X : Ω → ℝ} {c : NNReal} {μ : autoParam (MeasureTheory.Measure Ω) ProbabilityTheory.HasSubgaussianMGF._auto_1} (integrable_exp_mul : ∀ (t : ℝ), MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) μ) (mgf_le : ∀ (t : ℝ), ProbabilityTheory.mgf X μ t ≤ Real.exp (↑c * t ^ 2 / 2)) : ProbabilityTheory.HasSubgaussianMGF X c μ - ProbabilityTheory.Kernel.HasSubgaussianMGF.mgf_le 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {Ω' : Type u_2} {mΩ : MeasurableSpace Ω} {mΩ' : MeasurableSpace Ω'} {X : Ω → ℝ} {c : NNReal} {κ : ProbabilityTheory.Kernel Ω' Ω} {ν : autoParam (MeasureTheory.Measure Ω') ProbabilityTheory.Kernel.HasSubgaussianMGF._auto_1} (self : ProbabilityTheory.Kernel.HasSubgaussianMGF X c κ ν) : ∀ᵐ (ω' : Ω') ∂ν, ∀ (t : ℝ), ProbabilityTheory.mgf X (κ ω') t ≤ Real.exp (↑c * t ^ 2 / 2) - ProbabilityTheory.HasCondSubgaussianMGF.mgf_le 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {m mΩ : MeasurableSpace Ω} {hm : m ≤ mΩ} [StandardBorelSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsFiniteMeasure μ] {X : Ω → ℝ} {c : NNReal} (h : ProbabilityTheory.HasCondSubgaussianMGF m hm X c μ) : ∀ᵐ (ω' : Ω) ∂μ.trim hm, ∀ (t : ℝ), ProbabilityTheory.mgf X ((ProbabilityTheory.condExpKernel μ m) ω') t ≤ Real.exp (↑c * t ^ 2 / 2) - ProbabilityTheory.Kernel.HasSubgaussianMGF.mk 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {Ω' : Type u_2} {mΩ : MeasurableSpace Ω} {mΩ' : MeasurableSpace Ω'} {X : Ω → ℝ} {c : NNReal} {κ : ProbabilityTheory.Kernel Ω' Ω} {ν : autoParam (MeasureTheory.Measure Ω') ProbabilityTheory.Kernel.HasSubgaussianMGF._auto_1} (integrable_exp_mul : ∀ (t : ℝ), MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) (ν.bind ⇑κ)) (mgf_le : ∀ᵐ (ω' : Ω') ∂ν, ∀ (t : ℝ), ProbabilityTheory.mgf X (κ ω') t ≤ Real.exp (↑c * t ^ 2 / 2)) : ProbabilityTheory.Kernel.HasSubgaussianMGF X c κ ν - ProbabilityTheory.Kernel.HasSubgaussianMGF.of_rat 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {Ω' : Type u_2} {mΩ : MeasurableSpace Ω} {mΩ' : MeasurableSpace Ω'} {ν : MeasureTheory.Measure Ω'} {κ : ProbabilityTheory.Kernel Ω' Ω} {X : Ω → ℝ} {c : NNReal} (h_int : ∀ (t : ℝ), MeasureTheory.Integrable (fun ω => Real.exp (t * X ω)) (ν.bind ⇑κ)) (h_mgf : ∀ (q : ℚ), ∀ᵐ (ω' : Ω') ∂ν, ProbabilityTheory.mgf X (κ ω') ↑q ≤ Real.exp (↑c * ↑q ^ 2 / 2)) : ProbabilityTheory.Kernel.HasSubgaussianMGF X c κ ν - ProbabilityTheory.mgf_le_of_mem_Icc_of_integral_eq_zero 📋 Mathlib.Probability.Moments.SubGaussian
{Ω : Type u_1} {mΩ : MeasurableSpace Ω} {μ : MeasureTheory.Measure Ω} {X : Ω → ℝ} [MeasureTheory.IsProbabilityMeasure μ] {a b t : ℝ} (hm : AEMeasurable X μ) (hb : ∀ᵐ (ω : Ω) ∂μ, X ω ∈ Set.Icc a b) (hc : ∫ (x : Ω), X x ∂μ = 0) (ht : 0 < t) : ProbabilityTheory.mgf X μ t ≤ Real.exp ((↑‖b - a‖₊ / 2) ^ 2 * t ^ 2 / 2)
About
Loogle searches Lean and Mathlib definitions and theorems.
You can use Loogle from within the Lean4 VSCode language extension
using the Loogle command from the command palette. You can also try the
#loogle command from LeanSearchClient,
the CLI version, the Loogle
VS Code extension, the lean.nvim
integration or the Zulip bot.
Usage
Loogle finds definitions and lemmas in various ways:
By constant:
🔍Real.sin
finds all lemmas whose statement somehow mentions the sine function.By lemma name substring:
🔍"differ"
finds all lemmas that have"differ"somewhere in their lemma name.By subexpression:
🔍_ * (_ ^ _)
finds all lemmas whose statements somewhere include a product where the second argument is raised to some power.The pattern can also be non-linear, as in
🔍Real.sqrt ?a * Real.sqrt ?aIf the pattern has parameters, they are matched in any order. Both of these will find
List.map:
🔍(?a -> ?b) -> List ?a -> List ?b
🔍List ?a -> (?a -> ?b) -> List ?bBy main conclusion:
🔍|- tsum _ = _ * tsum _
finds all lemmas where the conclusion (the subexpression to the right of all→and∀) has the given shape.As before, if the pattern has parameters, they are matched against the hypotheses of the lemma in any order; for example,
🔍|- _ < _ → tsum _ < tsum _
will findtsum_lt_tsumeven though the hypothesisf i < g iis not the last.You can filter for definitions vs theorems: Using
⊢ (_ : Type _)finds all definitions which provide data while⊢ (_ : Prop)finds all theorems (and definitions of proofs).
If you pass more than one such search filter, separated by commas
Loogle will return lemmas which match all of them. The
search
🔍 Real.sin, "two", tsum, _ * _, _ ^ _, |- _ < _ → _
would find all lemmas which mention the constants Real.sin
and tsum, have "two" as a substring of the
lemma name, include a product and a power somewhere in the type,
and have a hypothesis of the form _ < _ (if
there were any such lemmas). Metavariables (?a) are
assigned independently in each filter.
The #lucky button will directly send you to the
documentation of the first hit.
Source code
You can find the source code for this service at https://github.com/nomeata/loogle. The https://loogle.lean-lang.org/ service is provided by the Lean FRO. Please review the Lean FRO Terms of Use and Privacy Policy.
This is Loogle revision 9f11169 serving mathlib revision 69fae59