Efron–Stein inequality
TheoremEfron–Stein inequality for a finite product weight#✓fully proved
Let \(\alpha\) be a finite nonempty set, let \(p : \alpha \to \mathbb{R}\) satisfy \(p(a) \ge 0\) for every \(a \in \alpha\) and \(\sum_{a \in \alpha} p(a) = 1\), let \(n \in \mathbb{N}\) and let \(f : \alpha^n \to \mathbb{R}\). For \(x = (x_1, \dots, x_n) \in \alpha^n\) write \(w(x) = \prod_{j=1}^{n} p(x_j)\), and for a coordinate \(i \in \{1, \dots, n\}\) and \(a \in \alpha\) let \(x^{(i,a)}\) be \(x\) with its \(i\)-th coordinate replaced by \(a\). Let \(\mu = \sum_{x \in \alpha^n} w(x) f(x)\). Then
theorem efron_stein_finite_iid_general
{α : Type*} [Fintype α] [Nonempty α]
{n : ℕ}
(p : α → ℝ)
(hp_nonneg : ∀ a, 0 ≤ p a)
(hp_sum : ∑ a : α, p a = 1)
(f : (Fin n → α) → ℝ) :
let μ : ℝ := ∑ x : Fin n → α, (∏ i : Fin n, p (x i)) * f x
let var_ : ℝ :=
∑ x : Fin n → α, (∏ i : Fin n, p (x i)) * (f x - μ) ^ 2
var_ ≤ (1 / 2 : ℝ) *
∑ i : Fin n, ∑ x : Fin n → α, ∑ a : α,
(∏ j : Fin n, p (x j)) * p a *
(f x - f (Function.update x i a)) ^ 2
Used by 1
TheoremEfron–Stein inequality for finite i.i.d. coordinates#✓fully proved
Let \(\alpha\) be a finite nonempty set, let \(p : \alpha \to \mathbb{R}\) satisfy \(p(a) \ge 0\) for every \(a \in \alpha\) and \(\sum_{a \in \alpha} p(a) = 1\), let \(n \in \mathbb{N}\) and let \(f : \alpha^n \to \mathbb{R}\). For \(x = (x_1, \dots, x_n) \in \alpha^n\) write \(w(x) = \prod_{j=1}^{n} p(x_j)\), and for a coordinate \(i \in \{1, \dots, n\}\) and \(a \in \alpha\) let \(x^{(i,a)}\) be \(x\) with its \(i\)-th coordinate replaced by \(a\). Let \(\mu = \sum_{x \in \alpha^n} w(x) f(x)\). Then
In words: the variance of \(f\) under the product weight is at most half the expected sum of squared differences under independent resampling of each coordinate.
theorem efron_stein_finite_iid
{α : Type*} [Fintype α] [DecidableEq α] [Nonempty α]
{n : ℕ}
(p : α → ℝ)
(hp_nonneg : ∀ a, 0 ≤ p a)
(hp_sum : ∑ a : α, p a = 1)
(f : (Fin n → α) → ℝ) :
let μ : ℝ := ∑ x : Fin n → α, (∏ i : Fin n, p (x i)) * f x
let var_ : ℝ :=
∑ x : Fin n → α, (∏ i : Fin n, p (x i)) * (f x - μ) ^ 2
var_ ≤ (1 / 2 : ℝ) *
∑ i : Fin n, ∑ x : Fin n → α, ∑ a : α,
(∏ j : Fin n, p (x j)) * p a *
(f x - f (Function.update x i a)) ^ 2
Sources
- B. Efron and C. Stein, "The Jackknife Estimate of Variance", Annals of Statistics 9 (1981), DOI 10.1214/aos/1176345462. It follows from
efron_stein_finite_iid_general; the instance[DecidableEq α]is unused and keeps the source's shape.
Uses 1
Loading dependency explorer…
The dependency explorer needs JavaScript and its graph data.