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Asymptotic normality of the residual correlogram in the continuous-time nonlinear regression model
Volume 8, Issue 1 (2021), pp. 93–113
Alexander Ivanov ORCID icon link to view author Alexander Ivanov details   Kateryna Moskvychova ORCID icon link to view author Kateryna Moskvychova details  

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https://doi.org/10.15559/20-VMSTA170
Pub. online: 21 December 2020      Type: Research Article      Open accessOpen Access

Received
28 July 2020
Revised
5 December 2020
Accepted
5 December 2020
Published
21 December 2020

Abstract

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.

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Keywords
Nonlinear regression model stationary Gaussian noise covariance function residual correlogram asymptotic normality

MSC2010
62J02 62F12 62M10

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