\(\alpha\)-optimal sampling plans for large acceptance numbers
type: Item
instance of: scholarly article
title: \(\alpha\)-optimal sampling plans for large acceptance numbers
zbMATH Open document ID: 0611.62126
DOI: 10.1007/BF01894755
author: Elart von Collani
published in: Metrika
publication date: 1986-01-01T00:00:00Z
full work available at URL: https://eudml.org/doc/176062
review text: Lots of size N are inspected without replacement by a single sampling plan (n,c) where n is the sample size and c the acceptance number. A cost model is assumed which is linear in the inspection costs and the terminal decision (acceptance or rejection of the lots). Incorporating the probability (called \(\alpha)\) that the actual lot quality is not worse than the break-even quality, a minimax-regret approach is pursued and mathematically elaborated. An approximate solution is derived for the case \(c>10\).
Mathematics Subject Classification ID: 62P30
zbMATH DE Number: 3988564
zbMATH Keywords: acceptance sampling by attributes
zbMATH Keywords: large acceptance number
zbMATH Keywords: alpha-optimal sampling plans
zbMATH Keywords: linear cost model
zbMATH Keywords: single sampling plan
zbMATH Keywords: minimax-regret approach
MaRDI profile type: Publication
cites work: Q3680142
cites work: Q3711596
cites work: Approximate a-optimal sampling plans
cites work: Q5571505
cites work: Sampling Inspection as a Minimum Loss Problem
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description: scientific article; zbMATH DE number 3988564