Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSomsak Chanaimen_US
dc.contributor.authorVladik Kreinovichen_US
dc.description.abstractIn practice, we often need to find regression parameters in situations when for some of the values, we have several results of measuring this same value. If we know the accuracy of each of these measurements, then we can use the usual statistical techniques to combine the measurement results into a single estimate for the corresponding value. In some cases, however, we do not know these accuracies, so what can we do? In this paper, we describe two natural approaches to solving this problem. In addition to describing general techniques, our results also provide a theoretical explanation for several semi-heuristic ideas proposed for solving an important particular case of this problem—the case when we deal with interval uncertainty.en_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEconomics, Econometrics and Financeen_US
dc.titleHow to Find the Dependence Based on Measurements with Unknown Accuracy: Towards a Theoretical Justification for Midpoint and Convex-Combination Interval Techniques and Their Generalizationsen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Systems, Decision and Controlen_US
article.volume427en_US University of Texas at El Pasoen_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.

Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.