Measurement Procedures for the Variance of a Normal Distribution

Elart von Collani, Dumitrescu Monica and Panaite Victorina
Additional contact information
Elart von Collani: University of Würzburg, Sanderring 2, D-970720 Würzburg, Germany
Dumitrescu Monica: University of Bucharest, Faculty of Mathematics, 14, Academiei St., 70109 Bucharest, Romania. mdumi@pro.math.unibuc.ro
Panaite Victorina: University of Bucharest, Faculty of Mathematics, 14, Academiei St., 70109 Bucharest, Romania. victorina@math.math.unibuc.ro

Stochastics and Quality Control, 2002, vol. 17, issue 2, 155-176

Abstract: Neyman prediction and measurement procedures have been discussed by E.v. Collani, M. Dumitrescu and their co-workers since 1999. These procedures offer optimal, however, computational rather intensive ways for predicting with respect to the future outcome of a random variable and measuring with respect to the actual value of a deterministic variable under the realistic condition that the range of variability of any involved variable is bounded.This paper presents an algorithm for constructing Neyman prediction and complete measurement procedures for the variance of a normal distribution (with known or unknown mean). A comparison with the traditional shortest confidence intervals is presented by means of a numerical example.The main advantages of the Neyman approach are the following:1.the unrealistic assumption of maximal and, hence, generally unbounded range of variability is abandoned,2.the measurements (= confidence intervals) are necessarily subsets of the bounded range of variability, and, therefore, unreasonable results are impossible,3.the point estimation is necessarily meaningful because it is associated with a confidence interval and a specified confidence level.

Keywords: Neyman procedures; predictions; measurements; point estimator; normal distribution (search for similar items in EconPapers)
Date: 2002
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/EQC.2002.155 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:ecqcon:v:17:y:2002:i:2:p:155-176:n:3

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/eqc/html

DOI: 10.1515/EQC.2002.155

Access Statistics for this article

Stochastics and Quality Control is currently edited by George P. Yanev

More articles in Stochastics and Quality Control from De Gruyter
Bibliographic data for series maintained by Peter Golla ().