import OAI.Combinatorics.LowSpaceSubsetSum.Counting.Deficiency import OAI.Combinatorics.BalancedRyser.Probability.FiniteUniformVariance namespace OAI /-! # Deficiency under sampling without replacement The variance estimate in the paper's deficiency lemma is a specialization of the finite completion-coupling theorem `Balanced.WithoutReplacement.finiteVariance_powersetCard_le`. Its probability space is exactly the uniform law on all size-`v` subsets of the supplied domain `U`, including the cases `v = 0` and `v = |U|`. -/ namespace LowSpaceSubsetSum open scoped BigOperators open Balanced.WithoutReplacement variable {ι : Type*} [Fintype ι] [DecidableEq ι] /-- Mean deficiency of a uniform size-`v` subset of `U`. -/ noncomputable def meanDeficiency (a : ι → ℤ) (U : Finset ι) (v : ℕ) : ℝ := 𝔼 V ∈ U.powersetCard v, deficiency a V /-- Variance for uniform sampling of exactly `v` indices, without replacement. -/ noncomputable def deficiencyVariance (a : ι → ℤ) (U : Finset ι) (v : ℕ) : ℝ := finiteVariance (U.powersetCard v) (deficiency a) theorem deficiency_exchange_bound (a : ι → ℤ) (S : Finset ι) {i j : ι} (hi : i ∈ S) (hj : j ∉ S) : |deficiency a S - deficiency a (insert j (S.erase i))| ≤ 1 := by have hj' : j ∉ S.erase i := fun h => hj (Finset.mem_erase.mp h).2 simpa only [Finset.insert_erase hi] using (deficiency_replacement_lipschitz a (Finset.notMem_erase i S) hj') /-- The paper's exact variance bound `Var(d(V)) ≤ v`. -/ theorem deficiencyVariance_le (a : ι → ℤ) (U : Finset ι) (v : ℕ) (hv : v ≤ U.card) : deficiencyVariance a U v ≤ v := by have h := finiteVariance_powersetCard_le U v (deficiency a) (c := 1) zero_le_one hv (by intro S _ _ i hi j _ hj exact deficiency_exchange_bound a S hi hj) simpa only [deficiencyVariance, one_pow, mul_one] using h theorem deficiency_centered_secondMoment_le (a : ι → ℤ) (U : Finset ι) (v : ℕ) (hv : v ≤ U.card) : (𝔼 V ∈ U.powersetCard v, (deficiency a V - meanDeficiency a U v) ^ 2) ≤ v := deficiencyVariance_le a U v hv /-- A direct finite Chebyshev bound for deviations from the mean deficiency. The left side is the exact probability under uniform size-`v` sampling. -/ theorem deficiency_tail_fraction_le (a : ι → ℤ) (U : Finset ι) (v : ℕ) (hv : v ≤ U.card) {t : ℝ} (ht : 0 < t) : (((U.powersetCard v).filter (fun V => t ≤ |deficiency a V - meanDeficiency a U v|)).card : ℝ) / (U.powersetCard v).card ≤ (v : ℝ) / t ^ 2 := by classical let D := U.powersetCard v let B := D.filter fun V => t ≤ |deficiency a V - meanDeficiency a U v| have hD : (0 : ℝ) < D.card := by exact_mod_cast (Finset.powersetCard_nonempty.mpr hv).card_pos have hpoint : ∀ V ∈ D, (if t ≤ |deficiency a V - meanDeficiency a U v| then t ^ 2 else 0) ≤ (deficiency a V - meanDeficiency a U v) ^ 2 := by intro V _ split_ifs with h · have hsq := (sq_le_sq₀ ht.le (abs_nonneg _)).mpr h simpa only [sq_abs] using hsq · exact sq_nonneg _ have htail : (B.card : ℝ) * t ^ 2 ≤ ∑ V ∈ D, (deficiency a V - meanDeficiency a U v) ^ 2 := by calc _ = ∑ V ∈ D, if t ≤ |deficiency a V - meanDeficiency a U v| then t ^ 2 else 0 := by rw [← Finset.sum_filter] simp [B] _ ≤ _ := Finset.sum_le_sum hpoint have hvar : (∑ V ∈ D, (deficiency a V - meanDeficiency a U v) ^ 2) ≤ (v : ℝ) * D.card := by have h := deficiency_centered_secondMoment_le a U v hv rw [Finset.expect_eq_sum_div_card] at h exact (div_le_iff₀ hD).mp h change (B.card : ℝ) / D.card ≤ (v : ℝ) / t ^ 2 exact (div_le_div_iff₀ hD (sq_pos_of_pos ht)).mpr (htail.trans hvar) /-- Measure-theoretic form for the actual uniform fixed-cardinality law. -/ theorem deficiency_uniform_variance_le [MeasurableSpace (Finset ι)] [MeasurableSingletonClass (Finset ι)] (a : ι → ℤ) (U : Finset ι) (v : ℕ) (hv : v ≤ U.card) : ProbabilityTheory.variance (deficiency a) (PMF.uniformOfFinset (U.powersetCard v) (Finset.powersetCard_nonempty.mpr hv)).toMeasure ≤ v := by rw [variance_uniformOfFinset] exact deficiencyVariance_le a U v hv end LowSpaceSubsetSum end OAI