openAI-math-dataset / lean /OAI /Probability /SKRatio /Matrices /ConditionalGaussianSquares.lean
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import Mathlib
import OAI.Probability.SKRatio.Matrices.WeightedGaussianSquares
namespace OAI
section
noncomputable section
open scoped BigOperators ENNReal NNReal Topology
open MeasureTheory ProbabilityTheory Filter Set Real
namespace SKRatio.MatrixNet
open SKRatioClock.Regression
attribute [local instance] Classical.propDecidable
lemma weighted_square_product_tail {A u c : ℝ}
(ht : ∀ {ι : Type} [Fintype ι] (s : Finset ι) (a : ι → ℝ),
(∀ i∈s, |a i|≤A) → ∀ {n : ℕ}, 0<n → s.card≤n →
standardArrayLaw ι {z | u ≤ |(∑ i∈s, a i*(z i^2-1))/(n:ℝ)|} ≤
ENNReal.ofReal (3*exp (-c*n)))
{Ω : Type*} [MeasurableSpace Ω] (μ : Measure Ω) [IsProbabilityMeasure μ]
{ι : Type} [Fintype ι] (s : Finset ι) (a : Ω → ι → ℝ)
(hma : ∀ i, Measurable (fun ω => a ω i)) (ha : ∀ ω i, i∈s → |a ω i|≤A)
{n : ℕ} (hn : 0<n) (hc : s.card≤n) :
(μ.prod (standardArrayLaw ι)) {p | u ≤ |(∑ i∈s, a p.1 i*(p.2 i^2-1))/(n:ℝ)|} ≤
ENNReal.ofReal (3*exp (-c*n)) := by
have hE : MeasurableSet {p : Ω × (ι → ℝ) |
u ≤ |(∑ i∈s, a p.1 i*(p.2 i^2-1))/(n:ℝ)|} := by
apply measurableSet_le measurable_const
apply Measurable.abs
apply Measurable.div_const
exact Finset.measurable_sum _ (fun i _ => ((hma i).comp measurable_fst).mul
(((measurable_pi_apply i).comp measurable_snd).pow_const 2 |>.sub measurable_const))
rw [Measure.prod_apply hE]
calc
_ ≤ ∫⁻ _ω : Ω, ENNReal.ofReal (3*exp (-c*n)) ∂μ :=
lintegral_mono (fun ω => ht s (a ω) (ha ω) hn hc)
_ = _ := by simp
theorem weighted_square_conditioned_tail {A u : ℝ} (hA : 0≤A) (hu : 0<u) :
∃ c : ℝ, 0<c ∧ ∀ {ι : Type} [Fintype ι] (s : Finset ι)
(a : ({i // i∉s} → ℝ) → s → ℝ),
(∀ i, Measurable (fun y => a y i)) → (∀ y i, |a y i|≤A) →
∀ {n : ℕ}, 0<n → s.card≤n →
standardArrayLaw ι {z | u ≤ |(∑ i : s,
a (fun j => z j) i * (z i^2-1))/(n:ℝ)|} ≤
ENNReal.ofReal (3*exp (-c*n)) := by
classical
obtain ⟨c,hc,ht⟩ := weighted_standard_square_tail hA hu
refine ⟨c,hc,?_⟩
intro ι _ s a hm ha n hn hs
let E : Set (({i // i∉s} → ℝ) × (s → ℝ)) :=
{p | u ≤ |(∑ i : s, a p.1 i*(p.2 i^2-1))/(n:ℝ)|}
have hE : MeasurableSet E := by
apply measurableSet_le measurable_const
apply Measurable.abs
apply Measurable.div_const
exact Finset.measurable_sum _ (fun i _ => ((hm i).comp measurable_fst).mul
(((measurable_pi_apply i).comp measurable_snd).pow_const 2 |>.sub measurable_const))
have hp := measurePreserving_piEquivPiSubtypeProd
(fun _ : ι => gaussianReal 0 1) (fun i => i∈s)
have hp' := Measure.measurePreserving_swap.comp hp
have he : {z : ι → ℝ | u ≤ |(∑ i : s, a (fun j => z j) i*(z i^2-1))/(n:ℝ)|} =
(fun z => ((fun j : {i // i∉s} => z j), (fun j : s => z j))) ⁻¹' E := rfl
rw [he]
have hmap : MeasurePreserving (fun z : ι → ℝ =>
((fun j : {i // i∉s} => z j), (fun j : s => z j)))
(standardArrayLaw ι) ((standardArrayLaw {i // i∉s}).prod (standardArrayLaw s)) := by
convert! hp' using 1
dsimp only [standardArrayLaw]
congr 1
congr 1
exact Subsingleton.elim _ _
rw [hmap.measure_preimage hE.nullMeasurableSet]
exact weighted_square_product_tail ht (standardArrayLaw {i // i∉s})
Finset.univ a hm (fun y i _ => ha y i) hn (by simpa using hs)
end SKRatio.MatrixNet
end
end
end OAI