Exact Bounds on Finite Populations of Interval Data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2005-06

AUTHORS

Scott Ferson, Lev Ginzburg, Vladik Kreinovich, Luc Longpré, Monica Aviles

ABSTRACT

In this paper, we start research into using intervals to bound the impact of bounded measurement errors on the computation of bounds on finite population parameters (“descriptive statistics”). Specifically, we provide a feasible (quadratic time) algorithm for computing the lower bound \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\underline{\sigma^2}$$\end{document} on the finite population variance function of interval data. We prove that the problem of computing the upper bound \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\sigma}^2$$\end{document} is, in general, NP-hard. We provide a feasible algorithm that computes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{\sigma}^2$$\end{document} under reasonable easily verifiable conditions, and provide preliminary results on computing other functions of finite populations. More... »

PAGES

207-233

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11155-005-3616-1

DOI

http://dx.doi.org/10.1007/s11155-005-3616-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034825891


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