EconPapers    
Economics at your fingertips  
 

Nonparametric Models and Their Estimation

Göran Kauermann ()
Additional contact information
Göran Kauermann: University of Bielefeld

Chapter 10 in Modern Econometric Analysis, 2006, pp 137-152 from Springer

Abstract: Abstract Nonparametric models have become more and more popular over the last two decades. One reason for their popularity is software availability, which easily allows to fit smooth but otherwise unspecified functions to data. A benefit of the models is that the functional shape of a regression function is not prespecified in advance, but determined by the data. Clearly this allows for more insight which can be interpreted on a substance matter level. This paper gives an overview of available fitting routines, commonly called smoothing procedures. Moreover, a number of extensions to classical scatterplot smoothing are discussed, with examples supporting the advantages of the routines.

Keywords: Unemployment Rate; Generalize Additive Model; Smoothing Parameter; Nonparametric Regression; Royal Statistical Society (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations: View citations in EconPapers (2)

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:978-3-540-32693-9_10

Ordering information: This item can be ordered from
http://www.springer.com/9783540326939

DOI: 10.1007/3-540-32693-6_10

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 ().

 
Page updated 2025-04-02
Handle: RePEc:spr:sprchp:978-3-540-32693-9_10