roseking's picture
Add lean source and binary files (part 125)
dd14c26 verified
Raw History Blame Contribute Delete
9.41 kB
import OAI.Probability.LatticePassage.ProductVariance
import Mathlib.MeasureTheory.Integral.Pi
namespace OAI
namespace CompanionFPP
open MeasureTheory ProbabilityTheory Finset
variable {α : Type*} [MeasurableSpace α] (μ : Measure α) [IsProbabilityMeasure μ]
lemma measurable_finCons (n : ℕ) :
Measurable (fun z : α × (Fin n → α) => (Fin.cons z.1 z.2 : Fin (n+1) → α)) := by
apply Measurable.of_eval
intro i
refine Fin.cases ?_ (fun j => ?_) i
· simpa using (measurable_fst : Measurable (Prod.fst : α × (Fin n → α) → α))
· simpa only [Function.comp_def, Fin.cons_succ] using (measurable_pi_apply j).comp (measurable_snd :
Measurable (Prod.snd : α × (Fin n → α) → (Fin n → α)))
lemma finCons_preserving (n : ℕ) :
MeasurePreserving (fun z : α × (Fin n → α) => Fin.cons z.1 z.2)
(μ.prod (Measure.pi (fun _ : Fin n => μ)))
(Measure.pi (fun _ : Fin (n+1) => μ)) := by
simpa only [MeasurableEquiv.piFinSuccAbove_symm_apply, Fin.insertNthEquiv,
Fin.insertNth_zero, Fin.zero_succAbove, Equiv.coe_fn_mk, cast_eq] using
(measurePreserving_piFinSuccAbove (fun _ : Fin (n+1) => μ) 0).symm
lemma integral_finCons {n : ℕ} {f : (Fin (n+1) → α) → ℝ}
(hf : Measurable f) {C : ℝ} (hC : ∀ v, |f v| ≤ C) :
(∫ v, f v ∂Measure.pi (fun _ : Fin (n+1) => μ)) =
∫ a, ∫ w, f (Fin.cons a w) ∂Measure.pi (fun _ : Fin n => μ) ∂μ := by
have he := integral_map (finCons_preserving μ n).aemeasurable hf.aestronglyMeasurable
rw [(finCons_preserving μ n).map_eq] at he
rw [he]
exact integral_prod _ ((bounded_memLp_two (hf.comp (measurable_finCons n))
C (fun z => hC (Fin.cons z.1 z.2))).integrable (by norm_num))
noncomputable def coordinateVariance {ι : Type*} [DecidableEq ι]
(f : (ι → α) → ℝ) (i : ι) (v : ι → α) : ℝ :=
variance (fun u => f (Function.update v i u)) μ
lemma measurable_coordinateVariance {ι : Type*} [Fintype ι] [DecidableEq ι]
{f : (ι → α) → ℝ} (hf : Measurable f) {C : ℝ} (hC : ∀ v, |f v| ≤ C) (i : ι) :
Measurable (coordinateVariance μ f i) := by
apply measurable_section_variance (C := C) (f := fun z => f (Function.update z.1 i z.2))
· exact hf.comp (by fun_prop)
· exact fun z => hC _
lemma coordinateVariance_bound {ι : Type*} [Fintype ι] [DecidableEq ι]
{f : (ι → α) → ℝ} (hf : Measurable f) {C : ℝ} (hC0 : 0 ≤ C)
(hC : ∀ v, |f v| ≤ C) (i : ι) (v : ι → α) :
|coordinateVariance μ f i v| ≤ C^2 := by
rw [coordinateVariance, abs_of_nonneg (variance_nonneg _ _)]
exact variance_le_bound_square (hf.comp (by fun_prop)) hC0 (fun _ => hC _)
lemma integrable_coordinateVariance {ι : Type*} [Fintype ι] [DecidableEq ι]
{f : (ι → α) → ℝ} (hf : Measurable f) {C : ℝ} (hC0 : 0 ≤ C)
(hC : ∀ v, |f v| ≤ C) (i : ι) :
Integrable (coordinateVariance μ f i) (Measure.pi (fun _ : ι => μ)) :=
(bounded_memLp_two (measurable_coordinateVariance μ hf hC i) (C^2)
(coordinateVariance_bound μ hf hC0 hC i)).integrable (by norm_num)
omit [IsProbabilityMeasure μ] in
lemma coordinateVariance_cons_zero {n : ℕ} (f : (Fin (n+1) → α) → ℝ)
(a : α) (w : Fin n → α) :
coordinateVariance μ f 0 (Fin.cons a w) = variance (fun u => f (Fin.cons u w)) μ := by
simp only [coordinateVariance, Fin.update_cons_zero]
omit [IsProbabilityMeasure μ] in
lemma coordinateVariance_cons_succ {n : ℕ} (f : (Fin (n+1) → α) → ℝ)
(i : Fin n) (a : α) (w : Fin n → α) :
coordinateVariance μ f i.succ (Fin.cons a w) =
coordinateVariance μ (fun v => f (Fin.cons a v)) i w := by
simp only [coordinateVariance, ← Fin.cons_update]
lemma integral_coordinateVariance_zero {n : ℕ} {f : (Fin (n+1) → α) → ℝ}
(hf : Measurable f) {C : ℝ} (hC0 : 0 ≤ C) (hC : ∀ v, |f v| ≤ C) :
(∫ v, coordinateVariance μ f 0 v ∂Measure.pi (fun _ : Fin (n+1) => μ)) =
∫ w, variance (fun u => f (Fin.cons u w)) μ ∂Measure.pi (fun _ : Fin n => μ) := by
rw [integral_finCons μ (measurable_coordinateVariance μ hf hC 0)
(coordinateVariance_bound μ hf hC0 hC 0)]
simp [coordinateVariance_cons_zero]
lemma integral_coordinateVariance_succ {n : ℕ} {f : (Fin (n+1) → α) → ℝ}
(hf : Measurable f) {C : ℝ} (hC0 : 0 ≤ C) (hC : ∀ v, |f v| ≤ C) (i : Fin n) :
(∫ v, coordinateVariance μ f i.succ v ∂Measure.pi (fun _ : Fin (n+1) => μ)) =
∫ a, ∫ w, coordinateVariance μ (fun v => f (Fin.cons a v)) i w
∂Measure.pi (fun _ : Fin n => μ) ∂μ := by
rw [integral_finCons μ (measurable_coordinateVariance μ hf hC i.succ)
(coordinateVariance_bound μ hf hC0 hC i.succ)]
simp only [coordinateVariance_cons_succ]
theorem variance_fin_le_sum_coordinateVariance (n : ℕ)
{f : (Fin n → α) → ℝ} (hf : Measurable f)
{C : ℝ} (hC0 : 0 ≤ C) (hC : ∀ v, |f v| ≤ C) :
variance f (Measure.pi (fun _ : Fin n => μ)) ≤
∑ i : Fin n, ∫ v, coordinateVariance μ f i v ∂Measure.pi (fun _ : Fin n => μ) := by
induction n with
| zero =>
have he : f = fun _ => f (fun i => Fin.elim0 i) := by
funext v
congr 1
funext i
exact Fin.elim0 i
rw [he]
simp [variance_eq_integral measurable_const.aemeasurable]
| succ n ih =>
let F := fun z : α × (Fin n → α) => f (Fin.cons z.1 z.2)
have hFm : Measurable F := hf.comp (measurable_finCons n)
have hFb : ∀ z, |F z| ≤ C := fun z => hC _
have he : variance f (Measure.pi (fun _ : Fin (n+1) => μ)) =
variance F (μ.prod (Measure.pi (fun _ : Fin n => μ))) := by
rw [← (finCons_preserving μ n).map_eq,
variance_map hf.aemeasurable (finCons_preserving μ n).aemeasurable]
rfl
rw [he]
have hv := product_variance_le (μ := μ) (ν := Measure.pi (fun _ : Fin n => μ))
hFm hC0 hFb
apply hv.trans
have hI : ∀ i : Fin n, Integrable (fun a => ∫ w,
coordinateVariance μ (fun v => f (Fin.cons a v)) i w
∂Measure.pi (fun _ : Fin n => μ)) μ := by
intro i
have hm := (measurable_coordinateVariance μ hf hC i.succ).comp (measurable_finCons n)
have hb := fun z : α × (Fin n → α) =>
coordinateVariance_bound μ hf hC0 hC i.succ (Fin.cons z.1 z.2)
have hi := (bounded_memLp_two (μ := μ.prod (Measure.pi (fun _ : Fin n => μ)))
hm (C^2) hb).integrable (by norm_num)
simpa only [Function.comp_def, coordinateVariance_cons_succ] using hi.integral_prod_left
have hstep := integral_mono (integrable_section_variance hFm hC0 hFb)
(integrable_finsetSum Finset.univ (fun i _ => hI i)) (fun a =>
ih (hf.comp ((measurable_finCons n).comp (measurable_const.prodMk measurable_id)))
(fun v => hC (Fin.cons a v)))
rw [integral_finsetSum _ (fun i _ => hI i)] at hstep
rw [Fin.sum_univ_succ, integral_coordinateVariance_zero μ hf hC0 hC]
simp_rw [integral_coordinateVariance_succ μ hf hC0 hC]
dsimp [F] at hstep ⊢
linarith
lemma reindex_preserving {ι κ : Type*} [Fintype ι] [Fintype κ] (e : κ ≃ ι) :
MeasurePreserving (fun v : κ → α => fun i => v (e.symm i))
(Measure.pi (fun _ : κ => μ)) (Measure.pi (fun _ : ι => μ)) := by
convert measurePreserving_piCongrLeft (fun _ : ι => μ) e using 1
funext v i
simp [MeasurableEquiv.coe_piCongrLeft, Equiv.piCongrLeft_apply]
omit [IsProbabilityMeasure μ] in
lemma coordinateVariance_reindex {ι κ : Type*} [Fintype ι] [Fintype κ]
[DecidableEq ι] [DecidableEq κ] (e : κ ≃ ι) (f : (ι → α) → ℝ) (j : κ) (v : κ → α) :
coordinateVariance μ (fun w => f (fun i => w (e.symm i))) j v =
coordinateVariance μ f (e j) (fun i => v (e.symm i)) := by
unfold coordinateVariance
congr 1
funext u
dsimp only
congr 1
funext i
by_cases hi : i = e j
· subst i
simp
· have hj : e.symm i ≠ j := by
intro h
apply hi
simpa using congrArg e h
simp [Function.update_of_ne hi, Function.update_of_ne hj]
theorem variance_pi_le_sum_coordinateVariance {ι : Type*} [Fintype ι] [DecidableEq ι]
{f : (ι → α) → ℝ} (hf : Measurable f)
{C : ℝ} (hC0 : 0 ≤ C) (hC : ∀ v, |f v| ≤ C) :
variance f (Measure.pi (fun _ : ι => μ)) ≤
∑ i : ι, ∫ v, coordinateVariance μ f i v ∂Measure.pi (fun _ : ι => μ) := by
let e : Fin (Fintype.card ι) ≃ ι := (Fintype.equivFin ι).symm
have hmp := reindex_preserving μ e
have hg := hf.comp hmp.measurable
have ht := variance_fin_le_sum_coordinateVariance μ (Fintype.card ι) hg hC0
(fun w => hC (fun i => w (e.symm i)))
simp only [Function.comp_def] at ht
rw [hmp.variance_fun_comp hf.aemeasurable] at ht
simp only [coordinateVariance_reindex] at ht
have he : ∀ j : Fin (Fintype.card ι),
(∫ w, coordinateVariance μ f (e j) (fun i => w (e.symm i))
∂Measure.pi (fun _ : Fin (Fintype.card ι) => μ)) =
∫ v, coordinateVariance μ f (e j) v ∂Measure.pi (fun _ : ι => μ) := by
intro j
have h := integral_map hmp.aemeasurable
(measurable_coordinateVariance μ hf hC (e j)).aestronglyMeasurable
rw [hmp.map_eq] at h
exact h.symm
simp_rw [he] at ht
rwa [e.sum_comp (fun i => ∫ v, coordinateVariance μ f i v ∂Measure.pi (fun _ : ι => μ))] at ht
end CompanionFPP
end OAI