Bootstrapping multiple linear regression after variable selection

Lasanthi C. R. Pelawa Watagoda () and David J. Olive ()
Additional contact information
Lasanthi C. R. Pelawa Watagoda: Appalachian State University
David J. Olive: Southern Illinois University

Statistical Papers, 2021, vol. 62, issue 2, No 6, 700 pages

Abstract: Abstract This paper suggests a method for bootstrapping the multiple linear regression model $$Y = \beta _1 + \beta _2 x_2 + \cdots + \beta _p x_p + e$$ Y = β 1 + β 2 x 2 + ⋯ + β p x p + e after variable selection. We develop asymptotic theory for some common least squares variable selection estimators such as forward selection with $$C_p$$ C p . Then hypothesis testing is done using three confidence regions, one of which is new. Theory suggests that the three confidence regions tend to have coverage at least as high as the nominal coverage if the sample size is large enough.

Keywords: Bagging; Confidence region; Forward selection (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s00362-019-01108-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:stpapr:v:62:y:2021:i:2:d:10.1007_s00362-019-01108-9

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-019-01108-9

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().