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.
ISBN: | 9783642421334 |
Publication date: | 23rd November 2014 |
Author: | James J Buckley |
Publisher: | Springer an imprint of Springer Berlin Heidelberg |
Format: | Paperback |
Pagination: | 168 pages |
Series: | Studies in Fuzziness and Soft Computing |
Genres: |
Probability and statistics Stochastics Artificial intelligence |