Some Non-asymptotic Rank Tests for Change Points in Regression
Silvelyn Zwanzig () and
Rauf Ahmad ()
Additional contact information
Silvelyn Zwanzig: Uppsala University, Department of Mathematics
Rauf Ahmad: Uppsala University, Department of Statistics
Chapter Chapter 13 in Asymptotic and Methodological Statistics, 2026, pp 257-274 from Springer
Abstract:
Abstract Rank-based tests for detecting the presence of change point in a linear regression model are presented. We build upon Theil’s idea, namely to consider the slope of all connecting lines, instead of the original points. We, however, use the idea to construct change point rank tests in regression in a way that it reduces the problem to a two-sample problem. Wilcoxon type tests are proposed, with ranks assigned to the pooled sample, whose exact distribution is known under the null hypothesis of no change point. Simple linear regression models are considered, for both fixed and random design. Extensions to multivariate and errors-in-variables models are discussed.
Date: 2026
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-07178-1_13
Ordering information: This item can be ordered from
http://www.springer.com/9783032071781
DOI: 10.1007/978-3-032-07178-1_13
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().