The Integer-Valued Moving-Average Random Field

Abstract An integer-valued moving average (INMA) model for count random fields is proposed and investigated. Closed-form expressions are derived for both its marginal distribution and spatial dependence structure, for arbitrary model order and also covering the multilateral case. In particular, general expressions for bivariate distributions and autocovariances are provided. It is shown that the INMA random field can be equipped (among others) with a Poisson marginal distribution. It is also demonstrated that different and well-interpretable dependence structures are possible. For illustration, we discuss a real-world data example and propose an INMA approximation to a given spatial dependence structure.

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Publication Details

Journal
Methodology And Computing In Applied Probability
Published
2026-08-20
DOI
https://doi.org/10.1007/s11009-026-10321-7
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

The Integer-Valued Moving-Average Random Field

Angelika Silbernagel, Christian H. Weiß
Methodology And Computing In Applied Probability
Statistical Distribution Estimation and Applications
article

The Integer-Valued Moving-Average Random Field

Angelika Silbernagel, Christian H. Weiß
article en

Abstract

Abstract An integer-valued moving average (INMA) model for count random fields is proposed and investigated. Closed-form expressions are derived for both its marginal distribution and spatial dependence structure, for arbitrary model order and also covering the multilateral case. In particular, general expressions for bivariate distributions and autocovariances are provided. It is shown that the INMA random field can be equipped (among others) with a Poisson marginal distribution. It is also demonstrated that different and well-interpretable dependence structures are possible. For illustration, we discuss a real-world data example and propose an INMA approximation to a given spatial dependence structure.

Methodology And Computing In Applied ProbabilityVol. 28(3)
Helmut Schmidt University (DE)
Reduced inequalities
Openalex Percentile: Top 60%
Statistical Distribution Estimation and Applications
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