A short introduction to splines in least squares regression analysis

Kathrin Kagerer

No 472, University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics

Abstract: Splines are an attractive way of flexibly modeling a regression curve since their basis functions can be included like ordinary covariates in regression settings. An overview of least squares regression using splines is presented including many graphical illustrations and comprehensive examples. Starting from two bases that are widely used for constructing splines, three different variants of splines are discussed: simple regression splines, penalized splines and smoothing splines. Further, restrictions such as monotonicity constraints are considered. The presented spline variants are illustrated and compared in a bivariate and a multivariate example with well-known data sets. A brief computational guide for practitioners using the open-source software R is given.

Keywords: B-spline; truncated power basis; derivative; monotonicity; penalty; smoothing spline; R (search for similar items in EconPapers)
JEL-codes: C14 C51 (search for similar items in EconPapers)
Date: 2013-03-28
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://epub.uni-regensburg.de/27968/1/DP472_Kagerer_introduction_splines.pdf (application/pdf)

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:bay:rdwiwi:27968

Access Statistics for this paper

More papers in University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Gernot Deinzer ().