 Change-point detection for the link function in a single-index modelQing Yang and Yi Zhang Statistics & Probability Letters, 2022, vol. 186, issue C Abstract: This article investigates the test size and power of a weighted-residual-based cumulative-sum (CUSUM) statistic for detecting the change of the link function in a single-index model. The asymptotic distributions of the CUSUM statistic are derived under the null hypothesis (when there is no change point) and the local alternative hypothesis (when there is a change with the size of order root n), and the importance of the weight function is analyzed further. Numerical performance of the test statistic is investigated using simulated data and is well satisfactory. In particular, as an extension, a single-index heterogeneous autoregressive model is built for the analysis of the realized volatilities of the S&P 500 index from 2016 to 2017, and 5 change points are detected by the proposed detection method. Keywords: CUSUM statistic; Kernel regression; Single-index model; Structural change (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:186:y:2022:i:c:s0167715222000608 Ordering information: This journal article can be ordered from DOI: 10.1016/j.spl.2022.109468 Access Statistics for this article Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul More articles in Statistics & Probability Letters from Elsevier |
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