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- Author: James J Buckley
- Publisher: Physica Verlag
- Year: 2012
- Pages: 165
- ISBN-10: 364286788X
- ISBN-13: 9783642867880
- Format: 15.6 x 23.4 x 1 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
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.
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- Author: James J Buckley
- Publisher: Physica Verlag
- Year: 2012
- Pages: 165
- ISBN-10: 364286788X
- ISBN-13: 9783642867880
- Format: 15.6 x 23.4 x 1 cm, minkšti viršeliai
- Language: English English
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.
Reviews