Statistical Estimates Obtained by the Minimal Distances Method

Svetlozar T. Rachev, Lev B. Klebanov, Stoyan V. Stoyanov and Frank J. Fabozzi
Additional contact information
Svetlozar T. Rachev: Stony Brook University, Department of Applied Mathematics and Statistics College of Business
Lev B. Klebanov: Charles University, Department of Probability and Statistics
Stoyan V. Stoyanov: EDHEC Business School EDHEC-Risk Institute
Frank J. Fabozzi: EDHEC Business School EDHEC-Risk Institute

Chapter Chapter 23 in The Methods of Distances in the Theory of Probability and Statistics, 2013, pp 571-579 from Springer

Abstract: Abstract The goals of this chapter are to: Consider the problem of parameter estimation by the method of minimal distances, Study the properties of the estimators.

Keywords: Minimum Distance Method; Negative Definite Kernel; Symmetric Unimodal Density; Bounded Influence Function; Semiparametric Estimation (search for similar items in EconPapers)
Date: 2013
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:978-1-4614-4869-3_23

Ordering information: This item can be ordered from
http://www.springer.com/9781461448693

DOI: 10.1007/978-1-4614-4869-3_23

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 ().