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Monte Carlo estimation for guaranteed-coverage non-normal tolerance intervals. (English) Zbl 0842.62078

Summary: We propose a Monte Carlo sampling algorithm for estimating guaranteed-coverage tolerance factors for non-normal continuous distributions with known shape but unknown location and scale. The algorithm is based on reformulating this root-finding problem as a quantile-estimation problem. The reformulation leads to a geometrical interpretation of the tolerance-interval factor. For arbitrary distribution shapes, we analytically and empirically investigate various relationships among tolerance-interval coverage, confidence, and sample size. [For errata see ibid. 1997]

MSC:

62N05 Reliability and life testing
62F25 Parametric tolerance and confidence regions
65C99 Probabilistic methods, stochastic differential equations
65C05 Monte Carlo methods

Software:

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References:

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