Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Concise Guide to StatisticsEstimation

A Concise Guide to Statistics: Estimation [Estimation is the inference of properties of a distribution from an observed random sample. Estimators can be derived by various approaches. To quantify the quality of a given estimate, confidence intervals can be computed; the bootstrap is a general purpose method for this. Vulnerability of some estimators to sample contaminations leads to robust alternatives.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Concise Guide to StatisticsEstimation

Download PDF
23 pages

Loading next page...
 
/lp/springer-journals/a-concise-guide-to-statistics-estimation-T4cD9LW9Ry
Publisher
Springer Berlin Heidelberg
Copyright
© Hans-Michael Kaltenbach 2012
ISBN
978-3-642-23501-6
Pages
29 –51
DOI
10.1007/978-3-642-23502-3_2
Publisher site
See Chapter on Publisher Site

Abstract

[Estimation is the inference of properties of a distribution from an observed random sample. Estimators can be derived by various approaches. To quantify the quality of a given estimate, confidence intervals can be computed; the bootstrap is a general purpose method for this. Vulnerability of some estimators to sample contaminations leads to robust alternatives.]

Published: Sep 17, 2011

Keywords: Maximum-likelihood; Confidence interval; Bootstrap

There are no references for this article.