Asymptotic normality of the residual correlogram in the continuous-time nonlinear regression model

Autor:	Alexander Ivanov, Kateryna Moskvychova
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Nonlinear regression model stationary Gaussian noise covariance function residual correlogram Asymptotic normality Applied mathematics. Quantitative methods T57-57.97 Mathematics QA1-939
Zdroj:	Modern Stochastics: Theory and Applications, Vol 8, Iss 1, Pp 93-113 (2020)
Druh dokumentu:	article
ISSN:	2351-6046 2351-6054
DOI:	10.15559/20-VMSTA170
Popis:	In a continuous time nonlinear regression model the residual correlogram is considered as an estimator of the stationary Gaussian random noise covariance function. For this estimator the functional central limit theorem is proved in the space of continuous functions. The result obtained shows that the limiting sample continuous Gaussian random process coincides with the limiting process in the central limit theorem for standard correlogram of the random noise in the specified regression model.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/5524971f10464f52819cb876352635e4 Zobrazit plný text záznamu View record in DOAJ