The LLN and CLT for U-statistics under cross-sectional dependence. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Sun, Yiguo
• Is Part Of: Journal of nonparametric statistics. Volume 32:Issue 1(2020)
• Page Start: 201
• Page End: 224
• Publication Date: 2020-01-02
• Subjects: CLT -- Kernel -- LLN -- spatial autoregressive models -- U-statistics; 62G10 -- 62G20; Nonparametric statistics -- Periodicals; 519.5
• DOI: 10.1080/10485252.2019.1711378
• Languages: English
• ISSNs: 1048-5252

Abstract

Abstract : In this paper we establish the law of large numbers (LLN) and central limit theorem (CLT) for second-order kernel-weighted U-statistics of cross-sectionally dependent variables. To illustrate the usefulness of our theorems, we apply the new LLN and CLT to nonparametric model misspecification testing in spatial regression framework. Monte Carlo simulations are used to assess the finite sample performance of our test statistic.