S-chart for non-gaussian variables

An S-chart with probability limits is constructed under the assumption that the quality characteristic under study has the exponential, Laplace or logistic distribution. Monte Carlo methods are used to estimate the factors for constructing the S-chart.

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Main Author: Sim, C.H.
Format: Article
Published: Taylor & Francis 2000
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Online Access:http://eprints.um.edu.my/26010/
https://doi.org/10.1080/00949650008811995
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spelling my.um.eprints.260102021-09-02T02:51:44Z http://eprints.um.edu.my/26010/ S-chart for non-gaussian variables Sim, C.H. QA Mathematics An S-chart with probability limits is constructed under the assumption that the quality characteristic under study has the exponential, Laplace or logistic distribution. Monte Carlo methods are used to estimate the factors for constructing the S-chart. Taylor & Francis 2000 Article PeerReviewed Sim, C.H. (2000) S-chart for non-gaussian variables. Journal of Statistical Computation and Simulation, 65 (1-4). pp. 147-156. ISSN 0094-9655 https://doi.org/10.1080/00949650008811995 doi:10.1080/00949650008811995
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA Mathematics
spellingShingle QA Mathematics
Sim, C.H.
S-chart for non-gaussian variables
description An S-chart with probability limits is constructed under the assumption that the quality characteristic under study has the exponential, Laplace or logistic distribution. Monte Carlo methods are used to estimate the factors for constructing the S-chart.
format Article
author Sim, C.H.
author_facet Sim, C.H.
author_sort Sim, C.H.
title S-chart for non-gaussian variables
title_short S-chart for non-gaussian variables
title_full S-chart for non-gaussian variables
title_fullStr S-chart for non-gaussian variables
title_full_unstemmed S-chart for non-gaussian variables
title_sort s-chart for non-gaussian variables
publisher Taylor & Francis
publishDate 2000
url http://eprints.um.edu.my/26010/
https://doi.org/10.1080/00949650008811995
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score 13.160551