import Mathlib import OAI.Probability.SKRatio.Matrices.GaussianAffineGaussianSup import OAI.Probability.SKRatio.Matrices.GaussianProductUpperTailLipschitz import OAI.Probability.SKRatio.Quantization.BinGaussian namespace OAI noncomputable section open scoped BigOperators Matrix NNReal open MeasureTheory ProbabilityTheory Filter Real namespace SKRatio.Bins variable {ι α : Type*} [Fintype ι] [Nonempty ι] [Fintype α] [DecidableEq α] attribute [local instance] Classical.propDecidable def average (p : ι → ℝ) : ℝ := (∑ i, p i)/(Fintype.card ι:ℝ) def centered (p : ι → ℝ) : ι → ℝ := fun i => p i-average p omit [Nonempty ι] in lemma average_add (p q : ι → ℝ) : average (fun i => p i+q i)=average p+average q := by simp only [average,Finset.sum_add_distrib,add_div] omit [Nonempty ι] in lemma average_mul (p : ι → ℝ) (c : ℝ) : average (fun i => c*p i)=c*average p := by simp only [average,←Finset.mul_sum,mul_div_assoc] lemma average_const (c : ℝ) : average (fun _ : ι => c)=c := by have hn : (Fintype.card ι:ℝ)≠0 := Nat.cast_ne_zero.mpr Fintype.card_ne_zero simp [average,mul_div_cancel_left₀ _ hn] omit [Nonempty ι] in lemma average_zeroSum {σ : ι → α} {u : ι → ℝ} (hu : ZeroSum σ u) : average u=0 := by have h := zero_sum_weighted hu (fun _ => 1) simpa only [mul_one, average, zero_div] using congrArg (fun z : ℝ => z/(Fintype.card ι:ℝ)) h lemma centered_sq (p : ι → ℝ) : (∑ i, centered p i^2)=(∑ i, p i^2)- (Fintype.card ι:ℝ)*average p^2 := by have hn : (Fintype.card ι:ℝ)≠0 := Nat.cast_ne_zero.mpr Fintype.card_ne_zero have hsum : (∑ i, p i)=(Fintype.card ι:ℝ)*average p := by dsimp [average] field_simp simp only [centered,sub_sq,Finset.sum_add_distrib,Finset.sum_sub_distrib, ←Finset.sum_mul,←Finset.mul_sum,Finset.sum_const,Finset.card_univ,nsmul_eq_mul] rw [hsum] ring lemma centered_sq_le (p : ι → ℝ) : (∑ i, centered p i^2)≤∑ i, p i^2 := by rw [centered_sq] exact sub_le_self _ (mul_nonneg (Nat.cast_nonneg _) (sq_nonneg _)) def fullCoeff (v p : ι → ℝ) (δ : ℝ) : Coordinates ι → ℝ | .inl (i,j) => δ/sqrt 2*(centered p i*centered (fun k => v k*p k) j+ centered p j*centered (fun k => v k*p k) i) | .inr _ => 0 omit [Nonempty ι] in lemma continuous_centered : Continuous (centered (ι := ι)) := by apply continuous_pi intro i exact (continuous_apply i).sub ((continuous_finsetSum _ (fun j _ => continuous_apply j)).div_const _) omit [Nonempty ι] in lemma continuous_fullCoeff (v : ι → ℝ) (δ : ℝ) : Continuous (fun p => fullCoeff v p δ) := by apply continuous_pi intro k cases k with | inr i => exact continuous_const | inl ij => change Continuous (fun p => δ/sqrt 2*(centered p ij.1*centered (fun k => v k*p k) ij.2+ centered p ij.2*centered (fun k => v k*p k) ij.1)) have hm : Continuous (fun p : ι → ℝ => fun k => v k*p k) := by fun_prop exact (((continuous_apply ij.1).comp continuous_centered |>.mul ((continuous_apply ij.2).comp (continuous_centered.comp hm))).add (((continuous_apply ij.2).comp continuous_centered).mul ((continuous_apply ij.1).comp (continuous_centered.comp hm)))).const_mul _ def crossCoeff (σ : ι → α) (v b : α → ℝ) (a d : α) : ℝ := (v a+v d)*b d-average (fun i => (v a+v (σ i))*b (σ i)) omit [Nonempty ι] [Fintype α] [DecidableEq α] in lemma crossCoeff_eq (σ : ι → α) (v b : α → ℝ) (a : α) (j : ι) : crossCoeff σ v b a (σ j)=centered (fun i => v (σ i)*b (σ i)) j+ v a*centered (fun i => b (σ i)) j := by have he : (fun i => (v a+v (σ i))*b (σ i))= (fun i => v a*b (σ i)+v (σ i)*b (σ i)) := by ext i; ring rw [crossCoeff,he,average_add,average_mul] dsimp only [centered] ring omit [Nonempty ι] in lemma centered_add_zeroSum {σ : ι → α} (b : α → ℝ) {u : ι → ℝ} (hu : ZeroSum σ u) : centered (fun i => b (σ i)+u i)=fun i => centered (fun k => b (σ k)) i+u i := by ext i simp only [centered,average_add,average_zeroSum hu,add_zero] ring omit [Nonempty ι] [Fintype α] in lemma zeroSum_mul {σ : ι → α} (v : α → ℝ) {u : ι → ℝ} (hu : ZeroSum σ u) : ZeroSum σ (fun i => v (σ i)*u i) := by intro a have he : sum σ (fun i => v (σ i)*u i) a = v a*sum σ u a := by unfold sum rw [Finset.mul_sum] apply Finset.sum_congr rfl intro i hi change v (σ i)*u i=v a*u i rw [(Finset.mem_filter.mp hi).2] rw [he,hu a,mul_zero] omit [Nonempty ι] in lemma fullCoeff_decomposition {σ : ι → α} (v b : α → ℝ) (δ : ℝ) {u : ι → ℝ} (hu : ZeroSum σ u) : fullCoeff (fun i => v (σ i)) (fun i => b (σ i)+u i) δ = fun k => fullCoeff (fun i => v (σ i)) (fun i => b (σ i)) δ k+ residualCoeff σ (crossCoeff σ v b) (fun a d => v a+v d) δ u k := by have he : (fun i => v (σ i)*(b (σ i)+u i))= fun i => v (σ i)*b (σ i)+v (σ i)*u i := by ext i; ring have hcen := centered_add_zeroSum (fun a => v a*b a) (zeroSum_mul v hu) ext k cases k with | inr i => simp [fullCoeff,residualCoeff] | inl ij => rcases ij with ⟨i,j⟩ simp only [fullCoeff,residualCoeff,centered_add_zeroSum b hu,he,hcen,residualMatrix, Matrix.add_apply,Matrix.transpose_apply,linearMatrix,quadraticMatrix,crossCoeff_eq] ring lemma fullCoeff_sq_le {v p : ι → ℝ} (hv : ∀ i, |v i|≤1) (δ : ℝ) : (∑ k, fullCoeff v p δ k^2) ≤ 2*δ^2*(∑ i, p i^2)^2 := by let x := centered p let y := centered (fun i => v i*p i) have hx : (∑ i, x i^2)≤∑ i, p i^2 := centered_sq_le p have hy : (∑ i, y i^2)≤∑ i, p i^2 := (centered_sq_le _).trans (by apply Finset.sum_le_sum intro i _ have hvi : v i^2≤1 := (sq_le_one_iff_abs_le_one (v i)).mpr (hv i) simpa only [mul_pow,one_mul] using mul_le_mul_of_nonneg_right hvi (sq_nonneg (p i))) have hprod : (∑ i, x i^2)*(∑ j, y j^2)≤(∑ i, p i^2)^2 := by rw [pow_two] exact mul_le_mul hx hy (Finset.sum_nonneg (fun _ _ => sq_nonneg _)) (Finset.sum_nonneg (fun _ _ => sq_nonneg _)) have hsq : (∑ i, ∑ j, (x i*y j+x j*y i)^2)≤4*((∑ i, x i^2)*(∑ j, y j^2)) := by calc _ ≤ ∑ i, ∑ j, 2*((x i*y j)^2+(x j*y i)^2) := by apply Finset.sum_le_sum intro i _ apply Finset.sum_le_sum intro j _ nlinarith only [sq_nonneg (x i*y j-x j*y i)] _ = _ := by simp only [mul_add,mul_pow,Finset.sum_add_distrib,←Finset.mul_sum,←Finset.sum_mul] ring simp only [Fintype.sum_sum_type,fullCoeff,zero_pow (by norm_num : (2:ℕ)≠0), Finset.sum_const_zero,add_zero,Fintype.sum_prod_type,mul_pow,div_pow, sq_sqrt (by norm_num : (0:ℝ)≤2),←Finset.mul_sum] change δ^2/2*(∑ i, ∑ j, (x i*y j+x j*y i)^2)≤_ have h := mul_le_mul_of_nonneg_left (hsq.trans (mul_le_mul_of_nonneg_left hprod (by norm_num))) (show 0≤δ^2/2 by positivity) convert h using 1 first | rfl | ring lemma fullCoeff_norm_le {v p : ι → ℝ} (hv : ∀ i, |v i|≤1) {δ : ℝ} (hδ : 0≤δ) (hp : ∑ i, p i^2=1) : ‖WithLp.toLp 2 (fullCoeff v p δ)‖≤ sqrt 2*δ := by have h := fullCoeff_sq_le (p := p) hv δ rw [hp] at h have he : ‖WithLp.toLp 2 (fullCoeff v p δ)‖^2=∑ k, fullCoeff v p δ k^2 := by simp only [EuclideanSpace.norm_sq_eq,Real.norm_eq_abs,sq_abs] have hs := sq_sqrt (show (0:ℝ)≤2 by norm_num) have hpos : 0≤ sqrt 2*δ := mul_nonneg (sqrt_nonneg _) hδ apply (sq_le_sq₀ (norm_nonneg _) hpos).mp rw [mul_pow,hs,he] simpa only [one_pow,mul_one] using h section Translation variable {κ I : Type*} [Fintype κ] [TopologicalSpace I] [CompactSpace I] [Nonempty I] lemma gaussianSup_add_common {a : I → κ → ℝ} (ha : Continuous a) (c : κ → ℝ) (g : κ → ℝ) : SKRatioGaussian.gaussianSup (fun _ : I => 0) (fun t k => c k+a t k) g = (∑ k, c k*g k)+SKRatioGaussian.gaussianSup (fun _ : I => 0) a g := by have hac : Continuous (fun t k => c k+a t k) := continuous_const.add ha have he (t : I) : SKRatioGaussian.gaussianAffine (fun _ : I => 0) (fun t k => c k+a t k) g t = (∑ k, c k*g k)+SKRatioGaussian.gaussianAffine (fun _ : I => 0) a g t := by simp only [SKRatioGaussian.gaussianAffine,add_mul,Finset.sum_add_distrib,zero_add] apply le_antisymm · apply SKRatioGaussian.gaussianSup_le continuous_const hac intro t rw [he] exact add_le_add le_rfl (SKRatioGaussian.gaussianAffine_le_gaussianSup continuous_const ha g t) · obtain ⟨t, ht, _⟩ := SKRatioGaussian.gaussianSup_attained continuous_const ha g rw [ht,←he] exact SKRatioGaussian.gaussianAffine_le_gaussianSup continuous_const hac g t lemma integral_gaussianSup_add_common {a : I → κ → ℝ} (ha : Continuous a) (c : κ → ℝ) : (∫ g, SKRatioGaussian.gaussianSup (fun _ : I => 0) (fun t k => c k+a t k) g ∂SKRatioGaussian.gaussianCoordinates κ) = ∫ g, SKRatioGaussian.gaussianSup (fun _ : I => 0) a g ∂SKRatioGaussian.gaussianCoordinates κ := by have hi (k : κ) : Integrable (fun g : κ → ℝ => c k*g k) (SKRatioGaussian.gaussianCoordinates κ) := ((SKRatioClock.Regression.coordinate_hasLaw k).hasGaussianLaw.integrable).const_mul _ simp_rw [gaussianSup_add_common ha c] rw [integral_add (integrable_finsetSum _ (fun k _ => hi k)) (SKRatioGaussian.integrable_gaussianSup continuous_const ha), integral_finsetSum _ (fun k _ => hi k)] have hm (k : κ) : (∫ g : κ → ℝ, c k*g k ∂SKRatioGaussian.gaussianCoordinates κ)=0 := by rw [integral_const_mul] change c k*(∫ g : κ → ℝ, g k ∂SKRatioClock.Regression.standardArrayLaw κ)=0 rw [SKRatioClock.Regression.coordinate_mean,mul_zero] simp only [hm,Finset.sum_const_zero,zero_add] end Translation variable {I : Type*} [TopologicalSpace I] [CompactSpace I] [Nonempty I] theorem full_sup_expectation_le (σ : ι → α) (v b : α → ℝ) {s : α → ℝ} {δ : ℝ} (hδ : 0≤δ) {u : I → ι → ℝ} (huc : Continuous u) (hu0 : ∀ t, ZeroSum σ (u t)) (hus : ∀ t, overlap σ (u t) (u t)=s) : (∫ g, SKRatioGaussian.gaussianSup (fun _ : I => 0) (fun t => fullCoeff (fun i => v (σ i)) (fun i => b (σ i)+u t i) δ) g ∂SKRatioGaussian.gaussianCoordinates (Coordinates ι)) ≤ ∑ a, δ*sqrt (radicalSq σ (crossCoeff σ v b) (fun a d => v a+v d) s a)* sqrt (s a)*sqrt ((Finset.univ.filter (fun i => σ i=a)).card : ℝ) := by have hd (t : I) := fullCoeff_decomposition v b δ (hu0 t) simp_rw [hd] have hi := integral_gaussianSup_add_common ((continuous_residualCoeff σ (crossCoeff σ v b) (fun a d => v a+v d) δ).comp huc) (fullCoeff (fun i => v (σ i)) (fun i => b (σ i)) δ) exact hi.trans_le (residual_sup_expectation_le σ _ _ (fun a d => add_comm _ _) hδ huc hu0 hus) theorem full_sup_lipschitz (v : ι → ℝ) (hv : ∀ i, |v i|≤1) {δ : ℝ} (hδ : 0≤δ) {p : I → ι → ℝ} (hpc : Continuous p) (hp : ∀ t, ∑ i, p t i^2=1) : LipschitzWith ⟨sqrt 2*δ,by positivity⟩ (fun g : EuclideanSpace ℝ (Coordinates ι) => SKRatioGaussian.gaussianSup (fun _ : I => 0) (fun t => fullCoeff v (p t) δ) g.ofLp) := by apply SKRatioGaussian.gaussianSup_lipschitz continuous_const ((continuous_fullCoeff v δ).comp hpc) intro t exact fullCoeff_norm_le hv hδ (hp t) theorem full_sup_tail (σ : ι → α) (v b : α → ℝ) (hv : ∀ a, |v a|≤1) {s : α → ℝ} {δ : ℝ} (hδ : 0<δ) {u : I → ι → ℝ} (huc : Continuous u) (hu0 : ∀ t, ZeroSum σ (u t)) (hus : ∀ t, overlap σ (u t) (u t)=s) (hp : ∀ t, ∑ i, (b (σ i)+u t i)^2=1) {a : ℝ} (ha : 0≤a) : (SKRatioGaussian.gaussianCoordinates (Coordinates ι)).real {g | (∑ d, δ*sqrt (radicalSq σ (crossCoeff σ v b) (fun a d => v a+v d) s d)* sqrt (s d)*sqrt ((Finset.univ.filter (fun i => σ i=d)).card : ℝ))+a ≤ SKRatioGaussian.gaussianSup (fun _ : I => 0) (fun t => fullCoeff (fun i => v (σ i)) (fun i => b (σ i)+u t i) δ) g} ≤ exp (-a^2/(π^2*δ^2)) := by let p : I → ι → ℝ := fun t i => b (σ i)+u t i have hpc : Continuous p := continuous_const.add huc let f := SKRatioGaussian.gaussianSup (fun _ : I => 0) (fun t => fullCoeff (fun i => v (σ i)) (p t) δ) have hL : (0:ℝ≥0) < ⟨sqrt 2*δ,by positivity⟩ := by change (0:ℝ) hv (σ i)) hδ.le hpc hp) hL ha have he := full_sup_expectation_le σ v b hδ.le huc hu0 hus have hsub : {g | (∑ d, δ*sqrt (radicalSq σ (crossCoeff σ v b) (fun a d => v a+v d) s d)* sqrt (s d)*sqrt ((Finset.univ.filter (fun i => σ i=d)).card : ℝ))+a ≤ f g} ⊆ {g | a ≤ f g-∫ y, f y ∂SKRatioGaussian.gaussianCoordinates (Coordinates ι)} := by intro g hg change _+a≤f g at hg change (∫ y, f y ∂SKRatioGaussian.gaussianCoordinates (Coordinates ι))≤_ at he change a≤f g-(∫ y, f y ∂SKRatioGaussian.gaussianCoordinates (Coordinates ι)) linarith only [hg,he] have hcont : Continuous f := SKRatioGaussian.continuous_gaussianSup continuous_const ((continuous_fullCoeff _ _).comp hpc) apply (measureReal_mono hsub).trans convert hc using 1 <;> try rfl apply congrArg Real.exp change -a^2/(π^2*δ^2) = -2*a^2/(π^2*(sqrt 2*δ)^2) rw [mul_pow,sq_sqrt (by norm_num : (0:ℝ)≤2)] ring end SKRatio.Bins end end OAI