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Add lean source and binary files (part 40)
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import OAI.Combinatorics.BooleanFunctions.Walsh
namespace OAI
open scoped BigOperators
noncomputable section
namespace SquareRootDegree
/-! ## Uniform finite conditioning, without measure-theoretic assumptions -/
theorem average_prod {α β : Type*} [Fintype α] [Fintype β] (f : α × β → ℝ) :
average f = average (fun x => average (fun y => f (x,y))) := by
simp only [average, Fintype.card_prod, Nat.cast_mul, mul_inv_rev,
Fintype.sum_prod_type, ← Finset.mul_sum]
ring
def updateSwap {ι α : Type*} [DecidableEq ι] (i : ι) :
((ι → α) × α) ≃ ((ι → α) × α) where
toFun p := (Function.update p.1 i p.2, p.1 i)
invFun p := (Function.update p.1 i p.2, p.1 i)
left_inv p := by
apply Prod.ext
· funext j; by_cases h : j = i <;> simp [h]
· simp
right_inv p := by
apply Prod.ext
· funext j; by_cases h : j = i <;> simp [h]
· simp
theorem average_update {ι α : Type*} [DecidableEq ι] [Fintype ι] [Fintype α] [Nonempty α]
(f : (ι → α) → ℝ) (i : ι) :
average (fun x => average (fun a => f (Function.update x i a))) = average f := by
classical
have h := average_equiv (updateSwap (α := α) i) (fun p => f p.1)
rw [average_prod, average_prod] at h
simpa [updateSwap, average_const] using h
def cell {α β : Type*} (F : α → β) (b : β) (x : α) : ℝ := by
classical
exact if F x = b then 1 else 0
def cellMass {α β : Type*} [Fintype α] (F : α → β) (b : β) : ℝ :=
average (cell F b)
def cellMoment {α β : Type*} [Fintype α] (F : α → β) (g : α → ℝ) (b : β) : ℝ :=
average (fun x => cell F b x * g x)
def conditionalValue {α β : Type*} [Fintype α] (F : α → β) (g : α → ℝ) (b : β) : ℝ :=
cellMoment F g b / cellMass F b
def conditionalAverage {α β : Type*} [Fintype α] (F : α → β) (g : α → ℝ) : α → ℝ :=
fun x => conditionalValue F g (F x)
theorem cellMoment_eq_zero_of_mass_eq_zero {α β : Type*} [Fintype α] [Nonempty α]
(F : α → β) (g : α → ℝ) (b : β) (h : cellMass F b = 0) :
cellMoment F g b = 0 := by
classical
have hc : ∀ x, cell F b x = 0 := by
intro x
have hs : ∑ x, cell F b x = 0 := by
unfold cellMass average at h
exact (mul_eq_zero.mp h).resolve_left (inv_ne_zero (Nat.cast_ne_zero.mpr Fintype.card_ne_zero))
exact (Finset.sum_eq_zero_iff_of_nonneg (fun x _ => by unfold cell; split <;> norm_num)).mp hs x (Finset.mem_univ x)
simp [cellMoment, hc]
theorem mass_mul_conditionalValue {α β : Type*} [Fintype α] [Nonempty α]
(F : α → β) (g : α → ℝ) (b : β) :
cellMass F b * conditionalValue F g b = cellMoment F g b := by
by_cases h : cellMass F b = 0
· simp [h, cellMoment_eq_zero_of_mass_eq_zero F g b h]
· simp [conditionalValue, field]
theorem average_mul_comp_eq_sum {α β : Type*} [Fintype α] [Fintype β]
(F : α → β) (g : α → ℝ) (h : β → ℝ) :
average (fun x => h (F x) * g x) = ∑ b, h b * cellMoment F g b := by
classical
simp only [cellMoment, ← average_const_mul, ← average_sum]
congr 1
funext x
simp [cell]
theorem cellMoment_conditionalAverage {α β : Type*} [Fintype α] [Nonempty α]
(F : α → β) (g : α → ℝ) (b : β) :
cellMoment F (conditionalAverage F g) b = cellMoment F g b := by
have he : (fun x => cell F b x * conditionalAverage F g x) =
(fun x => cell F b x * conditionalValue F g b) := by
funext x
unfold cell conditionalAverage
split_ifs with h
· rw [h]
· simp
rw [cellMoment, he, average_mul_const]
exact mass_mul_conditionalValue F g b
theorem conditionalAverage_projection {α β : Type*} [Fintype α] [Nonempty α] [Fintype β]
(F : α → β) (g : α → ℝ) (h : β → ℝ) :
average (fun x => h (F x) * conditionalAverage F g x) =
average (fun x => h (F x) * g x) := by
rw [average_mul_comp_eq_sum, average_mul_comp_eq_sum]
simp only [cellMoment_conditionalAverage]
theorem average_conditionalAverage {α β : Type*} [Fintype α] [Nonempty α] [Fintype β]
(F : α → β) (g : α → ℝ) : average (conditionalAverage F g) = average g := by
simpa using conditionalAverage_projection F g (fun _ => 1)
theorem conditionalAverage_sq {α β : Type*} [Fintype α] [Nonempty α] [Fintype β]
(F : α → β) (g : α → ℝ) :
average (fun x => conditionalAverage F g x ^ 2) =
average (fun x => conditionalAverage F g x * g x) := by
simpa only [conditionalAverage, pow_two] using
conditionalAverage_projection F g (conditionalValue F g)
theorem conditionalAverage_lower_bound {α β : Type*} [Fintype α] [Nonempty α] [Fintype β]
(F : α → β) (g : α → ℝ) (p : β → ℝ) :
average (fun x => g x ^ 2) - average (fun x => (g x - p (F x)) ^ 2) ≤
average (fun x => conditionalAverage F g x ^ 2) := by
have h := average_nonneg (fun x => sq_nonneg (conditionalAverage F g x - p (F x)))
have he : (fun x => (conditionalAverage F g x - p (F x)) ^ 2) =
(fun x => conditionalAverage F g x ^ 2 - 2 * (p (F x) * conditionalAverage F g x) +
p (F x) ^ 2) := by funext x; ring
have he' : (fun x => (g x - p (F x)) ^ 2) =
(fun x => g x ^ 2 - 2 * (p (F x) * g x) + p (F x) ^ 2) := by funext x; ring
rw [he, average_add, average_sub, average_const_mul, conditionalAverage_projection] at h
rw [he', average_add, average_sub, average_const_mul]
linarith
end SquareRootDegree
end
end OAI