A central limit theorem for the Euler integral of a Gaussian random field

作者：Naitzat Gregory^*; Adler Robert J

来源：Stochastic Processes and Their Applications, 2017, 127(6): 2036-2067.

DOI：10.1016/j.spa.2016.09.007

• Random field
• Euler integral
• Gaussian processes
• Central limit theorem

Euler integrals of deterministic functions have recently been shown to have a wide variety of possible applications, including signal processing, data aggregation and network sensing. Adding random noise to these scenarios, as is natural in the majority of applications, leads to a need for statistical analysis, the first step of which requires asymptotic distribution results for estimators. The first such result is provided in this paper, as a central limit theorem for the Euler integral of pure, Gaussian, noise fields.

• 出版日期2017-6