Technometrics · 1986 · 56 citations · 9 references
Natural SciencesComputer ScienceMathematicsAlgorithmsProbability TheoryStochastic ProcessesProbabilistic CombinatoricsProbability InequalitiesQueueing TheoryRandomized ComputationLower BoundsLower Bounds For Randomized AlgorithmsProbability Mass FunctionsRun Length AnalysisWorst-case Bounds
Upper and lower bounds are derived for the distribution of the run length N of both the one-sided and two-sided CUSUM schemes. Based upon a sequence of iterates Pr(N > 0), Pr(N > 1), …, bounds are constructed such that (m n −) i Pr(N > n) ≤ Pr(N > n + i) ≤ (m n +) i Pr(N > n) holds for all n, i = 1, 2,…, with constants 0 ≤ m n −; ≤ m n + ≤ 1 suitably chosen. The bounds converge monotonically in the sense that (m n −) i+1Pr(N > n) ≤ (m n+1 −) i Pr(N > n + 1), (m n +) i+1Pr(N > n) ≥ (m n+1 +) i Pr(N > n + 1), and, under some mild and natural conditions, . As a by-product, bounds are presented for the percentage points of the distribution function of N, for the average run length of the inspection scheme, for the standard deviation of N, and finally, for the probability mass function of N. Some numerical results are displayed to demonstrate the effkiency of the method.
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An approach to the probability distribution of cusum run length
D. Brook, D. A. Evans · Biometrika · 1972 · 882 citations