Introduction -- Fuzzy Sets -- Fuzzy Probability Theory -- Discrete Fuzzy Random Variables -- Fuzzy Queuing Theory -- Fuzzy Markov Chains -- Fuzzy Decisions Under Risk -- Continuous Fuzzy Random Variables -- Fuzzy Inventory Control -- Joint Fuzzy Probability Distributions -- Applications of Joint Distributions -- Functions of a Fuzzy Random Variable -- Functions of Fuzzy Random Variables -- Law of Large Numbers -- Sums of Fuzzy Random Variables -- Conclusions and Future Research -- Index.
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SUMMARY OR ABSTRACT
Text of Note
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.