Autocovariance varieties of moving average random fields. (March 2022)

• Record Type: Journal Article
• Authors: Améndola, Carlos; Pham, Viet Son
• Is Part Of: Journal of symbolic computation. Volume 109(2022)
• Page Start: 202
• Page End: 219
• Publication Date: 2022-03
• Subjects: 14Q15 -- 60G60 -- 62F10 -- 62M10 -- 62R01; Algebraic statistics -- Autocovariance function -- Moving average -- Maximum likelihood -- Algebraic variety; Mathematics -- Data processing -- Periodicals; Numerical analysis -- Data processing -- Periodicals; Automatic programming (Computer science) -- Periodicals; Mathématiques -- Informatique -- Périodiques; Analyse numérique -- Informatique -- Périodiques; Programmation automatique -- Périodiques; Automatic programming (Computer science); Mathematics -- Data processing; Numerical analysis -- Data processing; Periodicals; Electronic journals; 510.285
• DOI: 10.1016/j.jsc.2020.07.002
• Languages: English
• ISSNs: 0747-7171

Abstract

Abstract: We study the autocovariance functions of moving average random fields over the integer lattice Z d from an algebraic perspective. These autocovariances are parametrized polynomially by the moving average coefficients, hence tracing out algebraic varieties. We derive dimension and degree of these varieties and we use their algebraic properties to obtain statistical consequences such as identifiability of model parameters. We connect the problem of parameter estimation to the algebraic invariants known as euclidean distance degree and maximum likelihood degree. Throughout, we illustrate the results with concrete examples. In our computations we use tools from commutative algebra and numerical algebraic geometry.