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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Taylor & Francis
2000
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| 在線閱讀: | http://eprints.um.edu.my/26010/ https://doi.org/10.1080/00949650008811995 |
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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 |
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Universiti Malaya |
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UM Library |
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Institutional Repository |
| continent |
Asia |
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Malaysia |
| content_provider |
Universiti Malaya |
| content_source |
UM Research Repository |
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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 |
| _version_ |
1710675849917759488 |