Nonparametric Density Estimation in Action

Eggermont, P. P. B.; LaRiccia, V. N.

doi:10.1007/978-1-0716-1244-6_8

P. P. B. Eggermont² &
V. N. LaRiccia²

Part of the book series: Springer Series in Statistics ((SSS))

100 Accesses

Abstract

We have come to the end of a long road, and it is time to put nonparametric density estimation to work, in particular, the various procedures for smoothing parameter selection.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

eBook: USD 16.99; Price excludes VAT (USA)

Softcover Book: USD 219.99; Price excludes VAT (USA)

Hardcover Book: USD 219.99; Price excludes VAT (USA)

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Department of Food and Resource Economics, University of Delware, Newark, DE, 19716, USA
P. P. B. Eggermont & V. N. LaRiccia

Authors

P. P. B. Eggermont
View author publications
You can also search for this author in PubMed Google Scholar
V. N. LaRiccia
View author publications
You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. P. B. Eggermont .

Rights and permissions

Reprints and permissions

Copyright information

About this chapter

Cite this chapter

Eggermont, P.P.B., LaRiccia, V.N. (2001). Nonparametric Density Estimation in Action. In: Maximum Penalized Likelihood Estimation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-1244-6_8

Download citation

DOI: https://doi.org/10.1007/978-1-0716-1244-6_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-95268-0
Online ISBN: 978-1-0716-1244-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)

Publish with us

Policies and ethics