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.
| Autorius: | James J. Buckley |
| Serija: | Studies in Fuzziness and Soft Computing |
| Leidėjas: | Springer Berlin Heidelberg |
| Išleidimo metai: | 2005 |
| Knygos puslapių skaičius: | 180 |
| ISBN-10: | 3540250336 |
| ISBN-13: | 9783540250333 |
| Formatas: | Knyga kietu viršeliu |
| Kalba: | Anglų |
| Žanras: | Stochastics |
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