Possibilistic analysis of bayesian estimators when imprecise prior information is described by shadowed sets

1Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper deals with the problem of the analysis of results of Bayesian estimation when the prior information about possible values of estimated parameters is imprecise. We assume that this imprecision is described by the shadowed sets introduced by Pedrycz. The usage of shadowed sets dramatically simplifies all required computations, in comparison, e.g., to the case when it is described by fuzzy sets. A possibilistic methodology for the evaluation of such estimators is proposed. A practical cases of the estimation of reliability characteristics for the exponential distribution is considered.

Cite

CITATION STYLE

APA

Hryniewicz, O. (2018). Possibilistic analysis of bayesian estimators when imprecise prior information is described by shadowed sets. In Advances in Intelligent Systems and Computing (Vol. 642, pp. 238–247). Springer Verlag. https://doi.org/10.1007/978-3-319-66824-6_21

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free