Glivenko–Cantelli Theorem for the kernel error distribution estimator in the first-order autoregressive model

Fuxia Cheng

Statistics & Probability Letters, 2018, vol. 139, issue C, 95-102

Abstract: This paper considers the uniform strong consistency of the kernel estimator of the error cumulative distribution function (CDF) in the first-order autoregressive model. The classical Glivenko–Cantelli Theorem is extended to the residual based kernel smooth CDF estimator in the autoregressive model.

Keywords: Kernel estimator; Glivenko–Cantelli Theorem; CDF. Residuals; Autoregressive models (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:139:y:2018:i:c:p:95-102

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DOI: 10.1016/j.spl.2018.03.018

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