How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Spatial summary estimators
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Analyticity of Holomorphic Functions; Liouville and Morera
- Approximation and Compactness in C(K)
- Arc Length and Rectifiable Curves
- Areas of Elementary Plane Figures
- Banach Alaoglu Goldstine and Krein Milman
- Banach Algebras Spectrum and Holomorphic Functional Calculus
- Banach Valued Integration and the Radon Nikodym Property
- Binary Operations, Monoids, Groups and Subgroups
- Bochner Inversion and Plancherel on LCA Groups
- Bounded Linear Operators and Quotient Spaces
- Bounded Variation and the Riemann–Stieltjes Integral
- Character Groups and Elementary LCA Duals
- Compact Operators and Riesz Schauder Theory
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Coordinate and Path Transport
- Complex Differentiability and the Cauchy–Riemann Equations
- Complex Lp Spaces and Test-Function Conventions
- Complex Norms and Realification
- Complex Power Series and Analytic Functions
- Complex Subspace Realification
- Complexification, Realification and Real Structures
- Connectedness
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Continuous Functional Calculus for Self Adjoint and Normal Operators
- Contour Integration
- Convergence: Nets and Filters
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces Adjoint Operators and Annihilators
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Fubini and Change of Variables
- Function Space Topologies and the Exponential Law
- Fundamental Trigonometric Identities
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Gelfand Theory and Commutative C Star Algebras
- Goursat's Theorem and Cauchy's Theorem in a Convex Domain
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Haar Measure Existence and Uniqueness
- Hausdorff via the Diagonal
- Hereditary and Productive Behaviour of the Separation Axioms
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Infinite Product Measures and Kolmogorov Extension
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Line Integrals and the Gradient Theorem
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Modes of Convergence for Random Variables
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Norming and Separation under Hahn–Banach
- Order, Zorn's Lemma, and the Axiom of Choice
- Orthonormal Bases, Parseval and Fourier Series
- Outer Measure and the Caratheodory Extension Theorem
- Partitions of Unity and Paracompactness
- pi: the Equivalent Characterizations
- Pointwise Extended-Real Function Products
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Probability Spaces Random Variables and Expectation
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Radon Measures and the Riesz Markov Kakutani Theorem
- Random fields and variograms
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Signed and Complex Measures Hahn and Jordan
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Spectral measures and periodogram bias
- Stationary means and sample autocovariance
- Stone–Weierstrass in General
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Analytic Hahn Banach Theorem
- The Ascoli–Arzelà Theorem
- The Baire Principles of Functional Analysis
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Fundamental Group of the Circle
- The Fundamental Theorems of Calculus
- The Identity Theorem, the Maximum Principle and the Open Mapping Theorem
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The Winding Number and the Global Cauchy Theorem
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Uniform Spaces: the Three Definitions
- Urysohn's Lemma and the Tietze Extension Theorem
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
The Van Hove window and spatial-average claims assume Countable Choice , which makes every Borel window Lebesgue measurable; the boundary excesses are required to be Lebesgue measurable as well. This page defines Van Hove observation windows and their spatial averages, then proves unbiasedness and L2 consistency of the spatial mean when the stationary covariance is absolutely integrable. It defines pair-count lattice covariance and increment-based semivariogram estimators, establishing only their stated unbiasedness results. The regular-grid periodogram is treated as an estimator for the spectral measure of the sampled lattice field on its dual torus. The page makes no variance or distributional claim for the periodogram, and it does not identify the lattice spectrum with an unaliased continuous-space spectrum.
For a field observed at fixed regular-grid spacing, the spectral target is the aliased spectrum on the dual torus. A local sampling identity proves its exact relationship to a continuous-space density. Under AC and DC, suppose the periodized density has a bounded representative continuous at the target and agreeing there with the alias sum. With the kernel hypotheses of Vanishing bias of a smoothed regular-grid spatial periodogram and bandwidths and , the expectations of the physically normalized raw and smoothed estimates converge to the unaliased value exactly when every noncentral alias at the target is zero. A continuous density supported in a compact subset of the open Nyquist cube suffices for targets in that cube, as proved in Unaliased fixed-grid spectral bias under the exact no-alias condition. These are expectation limits only.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Van Hove sequences of spatial windows
Definition
Fix an integer and assume the Axiom of Countable Choice (The Axiom of Countable Choice ()). By Assuming countable choice, every Borel subset of is Lebesgue measurable, every Borel subset of is Lebesgue measurable under this assumption; by Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume, is the resulting complete Lebesgue measure. A Van Hove sequence of spatial windows is a sequence of bounded Borel sets (The Borel sigma-algebra of a topological space) in with for every , , and Here is Lebesgue measure when is Lebesgue measurable, and . As part of the condition, each boundary excess in the display is required to be Lebesgue measurable. Thus the window volume diverges while every fixed compact spatial enlargement adds a negligible relative volume.
Spatial window average
Definition
Let be a Van Hove sequence in as in Van Hove sequences of spatial windows, under its assumption. The Borel-measurability result makes each Lebesgue measurable, and the complete-measure result supplies the Lebesgue measure used below. On a probability space (Probability measures and probability spaces), let be a real random field in the coordinatewise sense of Random fields, stationarity, covariance, and variograms; its coordinates are real random variables (Random elements and real random variables) such that the map is measurable for (The Borel sigma-algebra of a topological space). For , assume that for almost every . Define the spatial window average on that full-measure event by and set it to on the measurable exceptional null set. Here and the integral use -dimensional Lebesgue measure, and a sample path means the function . The theorem Unbiasedness and L2 consistency of the spatial window average ↗ establishes this integrability and measurability from its stated second-moment hypotheses.
Unbiasedness and L2 consistency of the spatial window average
Statement
Assume the Axiom of Countable Choice , as required by Van Hove sequences of spatial windows. Let , , be a jointly measurable real random field on a probability space, with constant mean and finite second moments. Assume it is wide-sense stationary in the explicit sense that for all , and that . Let be a Van Hove sequence from Van Hove sequences of spatial windows. Then each spatial window average from Spatial window average is well-defined, satisfies and Thus these averages are unbiased and converge to the mean in . No variance consistency for any other estimator, weak consistency, or central limit theorem is asserted.
Facts & Assumptions
Given: , a probability space , a jointly measurable real field , , for every , stationary covariance , , and a Van Hove sequence .
Van Hove sequences of spatial windows: under , Assuming countable choice, every Borel subset of is Lebesgue measurable makes every Borel Lebesgue measurable and Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume supplies Lebesgue measure; every has finite positive volume, , and for each compact , .
Spatial window average: when a sample path is Lebesgue integrable, .
Random fields, stationarity, covariance, and variograms, Random elements and real random variables, and The Borel sigma-algebra of a topological space: a field is a family of real random variables on one probability space; joint measurability is an additional hypothesis for spatial integration, and wide stationarity supplies a constant mean and displacement-indexed covariance.
Moments, variance, and covariance on a probability space: variance is the expected centered square and covariance is the expected centered product; symmetry makes the reverse-lag convention in the Given equivalent to the supplier covariance convention.
Expectation of a nonnegative or integrable random variable: expectation is the Lebesgue integral against .
Cauchy-Schwarz for random variables: for , .
The product measure of two sigma-finite measure spaces and Tonelli's theorem for nonnegative measurable functions on a sigma-finite product: nonnegative product- measurable functions can be integrated in either order, and the section integral is measurable.
Integrable real and complex functions, and their integrals and Fubini's theorem for L^1 functions on a sigma-finite product: absolutely integrable product-measurable functions have equal iterated and product integrals.
Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation: Lebesgue measure is invariant under spatial translations.
convergence for random variables: convergence means that the norm of the difference tends to zero.
The product sigma-algebra and its finite iterates, A measurable function between measurable spaces, Every section of a product-measurable function is measurable, and Composition with a Borel measurable outer map preserves measurability: on , the maps and are measurable because the preimages of generating rectangles are respectively and . Composing with the jointly measurable field shows that and are measurable, so their centered product is measurable. Also, is continuous because . Every open subset of is a countable union of rational open rectangles, hence belongs to . Thus inverse images of open sets under addition are product-measurable, and the class of sets with product-measurable preimage is a sigma-algebra containing all open sets, hence contains every Borel set. Therefore addition is measurable for the product sigma-algebra and is measurable for Borel . Under AC in [A1], these Borel-measurable functions are also measurable for the product Lebesgue sigma-algebras used in Tonelli. Since is Lebesgue measurable by , its lift is measurable for the product Lebesgue sigma-algebra: the preimage of a Lebesgue-measurable set is . Thus is product-measurable as well.
Dominated convergence: pointwise convergence dominated by an integrable function permits passage of the limit through the integral.
Lebesgue measure is sigma-finite, and every metrically bounded subset of has finite outer measure: under the already assumed , Lebesgue measure on is sigma-finite, as witnessed by its increasing finite-measure cubes; its restriction to each bounded measurable is finite.
Proof
Proof technique: establish the exact covariance double integral, then use the Van Hove overlap limit and dominated convergence.
By [F11], Lebesgue measure on is sigma-finite under the assumed . Its restriction to is finite by [A1], and the probability measure has total mass . Thus all measure factors used below satisfy the sigma-finiteness hypotheses of [F5] and [F6], including the unbounded lag-space factor in . For every , [F4] with gives , where is constant by the stated first- and second-order stationarity. The map is product-measurable; Tonelli [F5] gives Therefore the sample path is absolutely integrable almost surely. Tonelli also makes the event where this integral is finite measurable; its probability is one. Applying Tonelli separately to and makes both section integrals measurable, and their difference on that event, extended by zero on its null complement as in [A2], is measurable.
Since , Fubini [F6] applies to on . Its constant mean gives
Put . The rectangle-preimage argument in [F9] makes product-measurable. By [F4], for all . Iterated Tonelli [F5] therefore gives a finite integral, at most , of the absolute pair product over . Each -section is integrable by this bound, so Fubini [F6] makes measurable; it equals by [F2]. A second Fubini calculation yields This also proves .
Define . The addition-measurability argument in [F9] makes product-measurable, so Tonelli [F5] gives measurability of its section integral . Also . For fixed , translation invariance [F7] gives The latter is bounded by , so the Van Hove condition [A1] implies .
The product-measurable integrand is absolutely integrable: Tonelli and [F9] give In the inner integral of step 1.3 set ; translation invariance [F7] gives . Fubini [F6] then yields The overlap factor is the measure of those for which .
Multiplying the formula in step 2.1 by gives By [F10], the right side converges to because . It is therefore bounded; since , step 2.1 implies .
The mean identity in step 1.2 and the second-moment limit in step 3.1 are exactly convergence to by [F8].
Lagged lattice covariance and variogram estimators
Definition
Let , let be a real random field (Random fields, stationarity, covariance, and variograms) whose coordinates are square-integrable real random variables on one probability space (Probability measures and probability spaces, Random elements and real random variables, Moments, variance, and covariance on a probability space, The integers as equivalence classes of pairs of naturals), and let be nonempty finite observation windows. Write and For a fixed lag , let Only indices with are admissible for this lag.
When the field is wide stationary in the sense of Random fields, stationarity, covariance, and variograms, write its constant mean as and its displacement covariance as , which is independent of by wide stationarity and agrees with the supplier convention by covariance symmetry. Define the pair-count-normalized raw-product covariance estimator by This convention subtracts the square of the one global sample mean from the pair-count-normalized raw product average; it is not the average of pairwise sample-centered products.
For the second-moment component of order-two intrinsic stationarity in Random fields, stationarity, covariance, and variograms, suppose the increments have finite second moments and is independent of ; define the empirical semivariogram by
Asymptotic unbiasedness of lattice covariance and variogram estimators
Statement
Let be real square-integrable random variables with constant mean and lag-dependent covariance independent of . Let be nonempty finite observation windows and assume that their sample means from Lagged lattice covariance and variogram estimators satisfy in . For each fixed with eventually, the pair-count-normalized raw-product covariance estimator satisfies
Separately, if the second moment of the lag- increment is independent of and equals , then the empirical semivariogram from Lagged lattice covariance and variogram estimators is exactly unbiased: for every with . These are expectation statements only; they assert no variance consistency, weak consistency, or central limit theorem.
Facts & Assumptions
Given: The lattice field, windows, fixed lag, and -consistent sample means in the Statement.
Lagged lattice covariance and variogram estimators: for and , and
Moments, variance, and covariance on a probability space: for square-integrable real random variables, covariance is the expectation of the centered product.
Linearity, monotonicity, and the modulus bound for expectation: expectation is linear on finite sums of integrable variables, and for integrable .
Cauchy-Schwarz for random variables: for square-integrable , , so is integrable.
convergence for random variables: in means .
Proof
Every product is integrable by [F3]. By the stationary covariance identity in the Given and [F1], for every .
By [F2], [F3] and [F4], because is bounded by and [F4].
Applying [F2] to the finite average in [A1] and using step 1.1 gives Step 1.2 therefore proves .
Under the increment-moment hypothesis, every summand in [A1] has expectation . Linearity [F2] over the pairs and division by give whenever the pair count is positive.
The integer lattice is a discrete locally compact abelian group
Statement
For every integer , equip with coordinatewise addition and its discrete topology. Then it is a locally compact Hausdorff abelian (topological) group. Every function from this discrete space to a topological space is continuous.
Facts & Assumptions
Given: An integer , coordinatewise addition on , and the discrete topology.
The integers form a commutative ring and Group and abelian group: addition on is an abelian group operation; in coordinates, the same associativity, commutativity, zero, and inverse laws hold on .
The discrete, indiscrete, cofinite, cocountable, particular-point and Sierpinski topologies: in the discrete topology every subset is open.
The product set of functions choosing a point in each factor, the projections, the box topology, and the product topology as the initial topology of the projections; the empty product is a one-point space: products have the product topology, whose basic open sets restrict coordinates by open subsets.
Continuity of a map of topological spaces at a point and globally: a map is continuous when its open-set preimages are open.
Topological group: multiplication and inversion are continuous: a group with a topology is a topological group when multiplication and inversion are continuous.
Hausdorff space: distinct points have disjoint open neighbourhoods; every metrizable space is Hausdorff and the indiscrete topology on two points is not: distinct points must have disjoint open neighbourhoods to be Hausdorff.
Open cover, subcover, and compact topological space; a compact subset is a subspace that is compact in its own right: every finite topological space, in particular a singleton, is compact.
Locally compact topological space: every point has a compact neighbourhood; and what this says in a metric space: a space is locally compact when each point has a compact neighbourhood.
Proof
The additive group of is abelian by [F1]. Coordinatewise addition on is associative and commutative, has the zero vector as identity, and sends to coordinatewise as its inverse. Hence is an abelian group.
For distinct , the singleton sets and are disjoint open neighbourhoods by [F2], so the space is Hausdorff by [F6]. Each singleton is finite and hence compact by [F7]; it is an open neighbourhood of by [F2]. Thus the space is locally compact by [F8].
The product topology on is discrete: for each pair , the basic open set is its singleton by [F2, F3]. Therefore coordinatewise addition and inversion are continuous by [F4]. By [F5] the group is a topological group, and with step 1.2 it is locally compact Hausdorff abelian. Every map from is continuous by [F2, F4].
The Pontryagin dual of the integer lattice is the torus
Statement
Give the discrete topology and let be the multiplicative unit circle. The map is a topological group isomorphism, where the dual has the compact-open topology and has the product topology.
Facts & Assumptions
Given: , the discrete additive group , the multiplicative unit circle , and the map in the Statement.
The Pontryagin dual with the compact-open topology: a character is a continuous group homomorphism to , and the dual consists of these characters with pointwise multiplication and the compact-open topology.
On a discrete domain the compact-open topology is the topology of pointwise convergence: on a discrete domain, the compact-open topology on the character set is the subspace topology inherited from ; in particular, evaluation at any fixed lattice point is continuous.
The integers as equivalence classes of pairs of naturals, The discrete, indiscrete, cofinite, cocountable, particular-point and Sierpinski topologies, Monoid homomorphism and group homomorphism, Integer powers in the complex field, and Exponent laws in a group: and for all , and when and commute: has the discrete topology, each has integer coordinates, a homomorphism preserves addition, and integer powers satisfy for .
The multiplicative unit circle is a compact metrizable topological abelian group and Topological group: multiplication and inversion are continuous and A map into a product is continuous iff each of its components is; the projections are continuous and open; and each projection is surjective when every factor is nonempty, which for an infinite index set uses the Axiom of Choice: is a topological abelian group, integer-power maps on it are continuous by repeated multiplication and inversion, and a map into a product is continuous when each coordinate map is continuous.
Homeomorphism, open map, closed map, embedding, and what it means for a property to be topological: a homeomorphism is a bijection that is continuous with continuous inverse.
The integer lattice is a discrete locally compact abelian group: with coordinatewise addition and the discrete topology is a Hausdorff locally compact abelian topological group; maps out of it are continuous.
Verification
For , the formula for is a homomorphism because for , It is continuous because its domain is discrete, so every preimage of an open set is open. Therefore .
The map is a group homomorphism because by [F3] and commutativity of [F4]. If , put , where is the th standard basis vector. Then by [F1], and the decomposition together with homomorphism and power laws gives . Thus ; also recovers each coordinate uniquely, so is bijective.
For each fixed , the coordinate map is a finite product of continuous integer-power maps on , hence continuous by [F4]. The product-topology criterion and [F2] then imply that is continuous into .
The inverse map is . Each coordinate is continuous by [F2], so the inverse is continuous into the finite product . Thus is a homeomorphism by [F5] and a group isomorphism by step 1.2 and the pointwise group law in [F1].
Transport of a lattice spectral measure to torus coordinates
Statement
Let be the homeomorphism from The Pontryagin dual of the integer lattice is the torus, and let be a finite positive Radon measure on . Define for every Borel set . Then is a finite positive Radon measure on , and for every bounded Borel function ,
Facts & Assumptions
Given: The homeomorphism and the finite positive Radon measure from the Statement.
The Pontryagin dual of the integer lattice is the torus: is a homeomorphism, so it and its inverse preserve Borel measurability, compactness and openness.
Radon measure on an LCH space: a Radon measure is finite on compact sets, outer regular on Borel sets and inner regular on open sets.
The Lebesgue integral is linear on , Every nonnegative measurable function is the increasing limit of simple measurable functions, and Monotone convergence for the integral: integrals of simple functions are linear, every nonnegative measurable function is the increasing limit of nonnegative measurable simple functions, and increasing limits pass through the integral.
The multiplicative unit circle is a compact metrizable topological abelian group, A product of finitely many compact spaces is compact in the product topology, and Arbitrary products preserve , , and Hausdorffness: is compact Hausdorff, hence locally compact Hausdorff.
Integrable real and complex functions, and their integrals: bounded Borel functions are integrable against the finite measures in the Statement.
Proof
Proof technique: define the transported measure and extend its integral identity from indicators.
If are pairwise disjoint Borel subsets of , then their images under the bijection are pairwise disjoint Borel sets by [F1]. Hence Thus is a positive measure, and .
For Borel and , outer regularity of gives an open with . Then is open, contains , and , proving outer regularity of . If is open in , inner regularity of gives compact with . Then is compact in and , proving inner regularity on open sets. The torus is compact Hausdorff by [F4], so these properties make Radon as in [F2].
For an indicator of a Borel set, Finite linearity [F3] extends this equality to Borel simple functions. For a nonnegative Borel function , the simple-approximation theorem [F3] supplies Borel simple functions . Since is continuous, measurably on the dual. Applying monotone convergence [F3] to the simple-function identity on both spaces gives the asserted identity for . Splitting the real and imaginary parts of a bounded complex Borel function into positive and negative parts then gives the stated identity by [F5].
Regular-grid spatial periodogram and smoothed estimator
Definition
Let satisfy the constant-mean, lag-dependent-covariance conditions from Lagged lattice covariance and variogram estimators, with known mean (set for a centered field), and use the frequency torus identified with by The Pontryagin dual of the integer lattice is the torus. Represent frequency coordinates by the circle tuple ; coordinates and integration are periodic modulo in each coordinate. For , set and let the Fourier-grid frequencies be The known-mean regular-grid periodogram is Integration over uses product angular Lebesgue measure on the fundamental cube (The product measure of two sigma-finite measure spaces).
For smoothing, let be continuous, even, compactly supported, and satisfy . For , periodize the rescaled kernel by Because has compact support, only finitely many summands are nonzero for each fixed , so this periodization is well-defined. For , when the denominator is positive, set The smoother is undefined when that denominator vanishes. Its target, when a spectral density exists, is the density of the lattice-sampled field on the dual torus; no unaliased continuous-space spectral-density target is part of this definition.
Fejer convolution formula for the lattice periodogram
Statement
Let and let be real square-integrable random variables with constant mean and lag-dependent covariance independent of . Assume the Axiom of Choice and Dependent Choice. Then there is a unique finite positive Radon measure on the angular torus such that For the periodogram of Regular-grid spatial periodogram and smoothed estimator, define the product Fejer kernel Then, for every and , The kernel is nonnegative and has integral one with respect to product angular Lebesgue measure. The spectral measure and density here belong to the lattice-indexed observations on the dual torus.
Facts & Assumptions
Given: The lattice field, constant mean, covariance convention, and periodogram definition in the Statement; assume AC and DC.
The Axiom of Choice: the Axiom of Choice is assumed.
The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain: Dependent Choice is assumed.
Positive definite functions on an abelian group: a function is positive definite when every finite quadratic form is nonnegative.
Bochner's theorem for LCA groups: under AC and DC, every continuous positive-definite function on an LCA group has a unique finite positive Radon representing measure on its Pontryagin dual.
The Pontryagin dual of the integer lattice is the torus: is identified with the product torus by .
Transport of a lattice spectral measure to torus coordinates: a finite positive Radon measure on transports to a finite positive Radon measure on while preserving integrals after composition.
Moments, variance, and covariance on a probability space: covariance is the expected centered product of square-integrable real random variables.
Linearity, monotonicity, and the modulus bound for expectation and Cauchy-Schwarz for random variables: expectation is linear on finite integrable sums, and products of square-integrable variables are integrable.
The product measure of two sigma-finite measure spaces and Fubini's theorem for L^1 functions on a sigma-finite product: the product angular Lebesgue measure exists and integrals can be evaluated by sections.
The integer lattice is a discrete locally compact abelian group: with the discrete topology is Hausdorff, abelian and locally compact, and every function on it is continuous.
Integer exponentials are orthogonal for angular Lebesgue measure: under Countable Choice, for every integer , is when and zero otherwise.
AC implies DC implies countable choice: AC implies Countable Choice (through DC).
The Axiom of Countable Choice (): Countable Choice selects one element from each set in a countable family of nonempty sets.
Proof
Proof technique: prove the covariance sequence is positive definite, apply Bochner on the discrete lattice, then expand the finite Fourier square.
For any finite lattice points and complex coefficients , the finite sum is square-integrable. Expanding its squared modulus, using [F6] and stationarity, gives Thus is positive definite by [F1].
By [F9], is a locally compact Hausdorff abelian group and every function on it is continuous, so is continuous. By Bochner's theorem [F2], using AC [A1] and DC [A2], there is a unique finite positive Radon measure on such that
Expand the finite squared modulus in [F5]. Every product is integrable by [F7], and stationarity gives
By [F3] and [F4], transport to the unique finite positive Radon measure on . Applying the integral-transport identity [F4] to gives
Substitute the spectral representation from step 2.1 into each summand of step 1.3. Linearity permits moving the finite sum through the integral, and After dividing by this is precisely
The displayed kernel factors into nonnegative one-dimensional kernels. For each coordinate, expanding the finite square and applying angular orthogonality [F10] to each integer exponent gives The Countable Choice hypothesis of [F10] follows from AC by [F11] and [A1]. Fubini [F8] for the finite product then gives and nonnegativity follows from the squared modulus.
Spectral alias identity for fixed regular-grid sampling
Statement
Assume AC and DC. Let , , be a real wide-stationary field with mean and covariance admitting the density representation where is a specified Borel representative. Fix spacing and sample , . On set This nonnegative measurable sum is finite almost everywhere, is in , and defines a periodic density of the sampled field's unique torus spectral measure: Thus for the angular periodogram of Fejer convolution formula for the lattice periodogram, The general fixed-grid target is this aliased density, without any alias-free assumption. Where a pointwise density limit is claimed, a version continuous at the target must be specified; a spectral measure alone supplies no canonical pointwise density value.
Facts & Assumptions
Given: AC and DC, the wide-stationary continuous-space field with its specified integrable nonnegative density, and fixed regular-grid spacing .
Random fields, stationarity, covariance, and variograms: wide stationarity gives a constant mean and displacement covariance; restricting to sites preserves these properties.
A linear map of sends Lebesgue measurable sets to Lebesgue measurable sets, with when is invertible and Lebesgue null when it is not and Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation: a scalar dilation by multiplies -dimensional Lebesgue measure by , and translations preserve it. The dilation theorem assumes Countable Choice.
Monotone convergence for the integral, Tonelli's theorem for nonnegative measurable functions on a sigma-finite product, Fubini's theorem for L^1 functions on a sigma-finite product, and Integrable real and complex functions, and their integrals: nonnegative countable sums pass through integrals, and absolutely integrable complex integrands can be partitioned and integrated termwise.
The multiplicative unit circle is a compact metrizable topological abelian group, A product of finitely many compact spaces is compact in the product topology, and Locally finite Borel measures on second-countable LCH spaces are regular: the finite-dimensional torus is compact Hausdorff and second-countable, and under Countable Choice its finite Borel measures are Radon. A countable base is obtained by intersecting rational Euclidean balls with its realization in .
Fejer convolution formula for the lattice periodogram: under AC and DC a stationary lattice covariance has a unique finite positive Radon torus spectral measure, and is its Fejer convolution.
The integers as equivalence classes of pairs of naturals and The integer-defining relation is an equivalence relation: is the quotient of by the stated equivalence relation. Let be an equivalence relation on with quotient map , and let . There is a function with if and only if implies ; and such a is then unique: the map sending a pair to its class is surjective. supplies a bijection . A nonempty set is at most countable iff it is a surjective image of : a nonempty set is at most countable if and only if it admits a surjection from . Every finite power of an at most countable set is at most countable: every finite power of an at most countable set is at most countable.
Every nonnegative measurable function is the increasing limit of simple measurable functions: every nonnegative measurable function is the increasing pointwise limit of nonnegative measurable simple functions.
The nonnegative Lebesgue integral: the nonnegative integral of a measurable function is the supremum of the integrals of its nonnegative simple minorants; for a simple function its integral is the finite sum over its disjoint level sets.
Proof
First establish the countability needed for the sum. By [F7], the quotient map is surjective, and is bijective. Their composite is onto: for any class , take a representative and the unique with ; then . Thus is at most countable by the surjection criterion in [F7]. Its finite power is at most countable by [F7] and is nonempty, since it contains the constant tuple with value (and for the empty tuple). The same criterion supplies a surjection . Put . These are increasing finite subsets whose union is . For a nonnegative family define its sum as . Each index is counted once, even if repeats values. Every finite subset of is contained in some : choose a preimage index for each of its finitely many elements and take their maximum. Hence the limit equals the supremum of all finite-subset sums and is invariant under reindexing. No countable family of choices is required. Each is nonnegative Borel. The finite partial sums over are Borel and increase; for each real , the strict superlevel set of their limit is the union of their Borel strict superlevel sets, so the limit is measurable. Reindexing the sum over finite subsets shows is periodic. The translates , , form a disjoint partition of . Put , so . Translation invariance [F2] first for indicators, then for simple functions by [F9] and by monotone convergence [F3] for nonnegative Borel functions, gives the cellwise integral translations. Monotone convergence [F3] then gives For the dilation identity, [F2] gives it first for indicators of Borel sets. For a nonnegative simple function written over disjoint level sets, summing these indicator identities gives the identity for the simple function by [F9]. By [F8], every nonnegative Borel function is an increasing limit of simple functions; monotone convergence [F3] therefore extends the dilation identity to every such function, including . Thus The measurable set where is null: if it had positive measure, the integral would be at least times that measure for every , contradicting finiteness. This set is periodic, so a finite-valued representative obtained by replacing by zero there remains periodic and defines the same measure.
For integer , the identity and the finite mass in step 1.1 permit the same increasing finite-union partition for the absolutely integrable complex integrand. Translation on each cell, using the integral- translation identity established in step 1.1 on the nonnegative parts of its real and imaginary parts, gives To apply dilation to this complex integral, write as the differences of its nonnegative cosine and sine parts. Apply the nonnegative scaling identity established in step 1.1 to , , and the corresponding two sine parts. Each is Borel and bounded by , hence integrable; recombining their integrals yields The density defines a finite Borel measure on the torus, Radon by [F5] and [F4]. By [F1] the sample is a stationary lattice field; symmetry of real covariance identifies with . Uniqueness in [F6] identifies that measure with its torus spectrum. The mass identity at is .
Apply [F6] to the sampled spectrum in step 2.1 to obtain the first periodogram expectation identity. Since is periodic, bounded for each fixed , and nonnegative, partitioning the density integral exactly as in step 1.1 gives its second expression over . That expression integrates a periodic kernel against the original density and does not remove the noncentral translates.
Source notes
Spodarev's finite-grid calculation in Lemma 2.10(b) produces the last periodic-kernel integral. Its subsequent unconditional claim of convergence to the unaliased continuous-space density omits periodization. The local identity supplies the correct target; the alias-free bias result is a separate corollary with an explicit exact condition.
Vanishing bias of a smoothed regular-grid spatial periodogram
Statement
Assume the Axiom of Choice and Dependent Choice, as in Fejer convolution formula for the lattice periodogram. Let the lattice spectral measure from that theorem be absolutely continuous with a specified bounded representative continuous at the chosen target frequency . Let and be as in Regular-grid spatial periodogram and smoothed estimator, and let satisfy Then the denominator defining is positive for all sufficiently large , and This is an asymptotic-bias statement only; it asserts no variance limit, weak consistency, or central limit theorem.
Facts & Assumptions
Given: The known-mean regular-grid periodogram, periodized kernel , bandwidth sequence, and continuous bounded spectral density in the Statement. For angular representatives define and for define .
Regular-grid spatial periodogram and smoothed estimator: the normalized Fourier-grid weights are and when the denominator is positive.
The Axiom of Choice: the Axiom of Choice is assumed for the imported Bochner representation.
The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain: Dependent Choice is also assumed for that representation, as in the preceding Fejer theorem.
Fejer convolution formula for the lattice periodogram: the expected raw periodogram is , where and .
Signs, monotonicity intervals, and ranges of sine and cosine and Pi is the first positive zero of sine: sine is increasing on and positive on , so for .
Linearity, monotonicity, and the modulus bound for expectation: expectation passes through the finite weighted sum defining the smoother.
The product measure of two sigma-finite measure spaces and Fubini's theorem for L^1 functions on a sigma-finite product: product angular measure and iterated integrals for the product Fejer kernel use the stated Lebesgue product measure.
Proof
Proof technique: control the Fejer mass outside neighborhoods, then use the kernel support and Fourier-grid mesh to localize the smoothing weights.
Write , so by [F1]. Fix . If the circular distance of from is at least , choose its representative in ; then by [F2]. The finite geometric-series formula therefore gives By the union bound over coordinates and the unit integral of each factor from [F1], where is the maximum circular distance over the coordinates.
Fix . Continuity of at gives such that whenever . For any with , split the convolution in [F1] into that neighborhood and its complement. On the neighborhood its contribution to is at most because has integral one. On the complement, ; with , step 1.1 gives This bound holds uniformly for all such .
Since is continuous and , there is such that whenever . A nearest Fourier-grid point to is within in each circular coordinate. Since , eventually , so the periodized kernel is positive at that grid point and the denominator in [A1] is positive. Moreover, if a weight in [A1] is positive, compact support of implies its grid point is within circular distance of in every coordinate, where contains the support of . Since , all positive-weight grid points eventually lie within the -neighborhood from step 2.1.
For all sufficiently large , [F3] and [A1] give The weights are nonnegative and sum to one, and every positive weight is on a grid point covered by step 2.1. Hence Taking and then arbitrary proves the smoothed bias limit. Taking in step 2.1 proves the raw expectation limit as well.
Unaliased fixed-grid spectral bias under the exact no-alias condition
Statement
Assume the model and AC/DC of Spectral alias identity for fixed regular-grid sampling. Fix , and put modulo . Suppose the pointwise periodized sum has a bounded torus representative continuous at , agreeing with that sum at . Use the kernel and bandwidths of Vanishing bias of a smoothed regular-grid spatial periodogram. Define the physically normalized estimates at by Then the smoother is defined eventually and both expectations converge to In particular, both have vanishing bias for the unaliased value if and only if This exact pointwise condition does not restrict the general aliased-target theorem. A sufficient global condition is that is continuous and supported in a compact subset of the open Nyquist cube , with in that cube. No variance, consistency or CLT conclusion is asserted.
Facts & Assumptions
Given: The fixed-spacing continuous-space model, a bounded periodized density representative continuous at the target and agreeing there with its sum, the kernel/bandwidth assumptions, and AC/DC.
Spectral alias identity for fixed regular-grid sampling: is the torus density of the sampled field and its pointwise sum is .
Vanishing bias of a smoothed regular-grid spatial periodogram: for a bounded torus density continuous at the chosen target, both raw and smoothed periodogram expectations converge to that density value; smoothing denominators are eventually positive.
Regular-grid spatial periodogram and smoothed estimator: the normalized Fourier-grid smoother is the specified finite nonnegative weighted sum of angular periodogram ordinates.
The Axiom of Choice and The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain: AC and DC are inherited through the lattice spectral representation and its bias theorem.
Proof
By [F1] the sampled field has torus density , and the assumed representative meets all hypotheses of [F2]. Thus the denominator in [F3] is eventually positive and both angular expectations tend to . Multiplying by and reindexing the convergent nonnegative sum at the target gives . This proves the general aliased limit for both physically normalized estimates.
Every alias summand is nonnegative. Therefore is zero if and only if every summand is zero. This proves both directions of the stated exact condition. Under the sufficient global condition, only the central translate is nonzero for frequencies in the Nyquist cube; its support stays away from the boundary. Hence the periodic density is bounded and continuous across the boundary as well, and has no noncentral alias at the stated target. All hypotheses and the exact condition are then verified.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Section 2.1
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Section 2.1, Example 2.1
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Lemmas 2.2–2.3 and Theorem 2.5
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Section 2.2
- Dennis Sun, Stanford Stats 253 Lecture 6: Covariance Estimation (2014), pp. 8–15
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Lemma 2.8 and Section 2.2
- Oxford Mathematical Institute, Harmonic Analysis lecture notes, characters of Z^d, Section 2.1, pp. 17–18
- Oxford Mathematical Institute, Harmonic Analysis lecture notes, characters of Z^d, pp. 17–18
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Section 2.3, Definitions 2.9–2.11
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Section 2.3, Definition 2.9 and Lemma 2.10
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Section 2.3, Definition 2.9(b) and the periodic-kernel calculation in Lemma 2.10(b), PDF pp. 20–21; fixed-grid target corrected locally
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Lemmas 2.10 and 2.14
- Evgeny Spodarev, Spatial Statistics: Lecture Notes (2024), Lemmas 2.10(b) and 2.14, PDF pp. 20–21 and 24; fixed-spacing continuous target supplied with its exact alias condition