Fuzzy Probabilities: New Approach and Applications

In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability...

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Beteilige Person: Buckley, James J. (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Heidelberg Physica-Verlag HD 2003
Schriftenreihe:Studies in Fuzziness and Soft Computing 115
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Links:https://doi.org/10.1007/978-3-642-86786-6
https://doi.org/10.1007/978-3-642-86786-6
https://doi.org/10.1007/978-3-642-86786-6
Zusammenfassung:In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory
Umfang:1 Online-Ressource (XII, 165p. 36 illus)
ISBN:9783642867866
DOI:10.1007/978-3-642-86786-6