Extension of Latin hypercube samples with correlated variables
A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2 m that contains the elements of the origi...
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| Veröffentlicht in: | Reliability engineering & system safety 2008-07, Vol.93 (7), p.1047-1059 |
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| container_title | Reliability engineering & system safety |
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| creator | Sallaberry, C.J. Helton, J.C. Hora, S.C. |
| description | A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size
m and associated rank correlation matrix
C and constructs a new LHS of size 2
m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix
C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations. |
| doi_str_mv | 10.1016/j.ress.2007.04.005 |
| format | Article |
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C and constructs a new LHS of size 2
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C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.</description><identifier>ISSN: 0951-8320</identifier><identifier>EISSN: 1879-0836</identifier><identifier>DOI: 10.1016/j.ress.2007.04.005</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Applied sciences ; Exact sciences and technology ; Experimental design ; Latin hypercube sample ; Mathematics ; Monte Carlo analysis ; Operational research and scientific management ; Operational research. Management science ; Probability and statistics ; Rank correlation ; Reliability theory. Replacement problems ; Sample size extension ; Sciences and techniques of general use ; Sensitivity analysis ; Statistics ; Uncertainty analysis</subject><ispartof>Reliability engineering & system safety, 2008-07, Vol.93 (7), p.1047-1059</ispartof><rights>2007</rights><rights>2008 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c405t-6403f7f6912743aef325abf76c4959f12113e73016dc9be72448bb6bacef29503</citedby><cites>FETCH-LOGICAL-c405t-6403f7f6912743aef325abf76c4959f12113e73016dc9be72448bb6bacef29503</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0951832007001378$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,65309</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20178467$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Sallaberry, C.J.</creatorcontrib><creatorcontrib>Helton, J.C.</creatorcontrib><creatorcontrib>Hora, S.C.</creatorcontrib><title>Extension of Latin hypercube samples with correlated variables</title><title>Reliability engineering & system safety</title><description>A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size
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C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.</description><subject>Applied sciences</subject><subject>Exact sciences and technology</subject><subject>Experimental design</subject><subject>Latin hypercube sample</subject><subject>Mathematics</subject><subject>Monte Carlo analysis</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Probability and statistics</subject><subject>Rank correlation</subject><subject>Reliability theory. Replacement problems</subject><subject>Sample size extension</subject><subject>Sciences and techniques of general use</subject><subject>Sensitivity analysis</subject><subject>Statistics</subject><subject>Uncertainty analysis</subject><issn>0951-8320</issn><issn>1879-0836</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EEqXwBzjlAreE9SNxLCEkhMpDqsQFzpbjrFVXaVLstNB_j6tWHDntYb-Z3RlCrikUFGh1tywCxlgwAFmAKADKEzKhtVQ51Lw6JRNQJc1rzuCcXMS4BAChSjkhD7OfEfvohz4bXDY3o--zxW6NwW4azKJZrTuM2bcfF5kdQsDOjNhmWxO8adLmkpw500W8Os4p-XyefTy95vP3l7enx3luBZRjXgngTrpKUSYFN-g4K03jZGXTF8pRRilHyVOS1qoGJROibpqqMRYdUyXwKbk9-K7D8LXBOOqVjxa7zvQ4bKKmqmJKUZVAdgBtGGIM6PQ6-JUJO01B76vSS72vSu-r0iB0qiqJbo7uJlrTuWB66-OfkgGVtahk4u4PHKaoW49BR-uxt9j6gHbU7eD_O_MLDZx_Gg</recordid><startdate>20080701</startdate><enddate>20080701</enddate><creator>Sallaberry, C.J.</creator><creator>Helton, J.C.</creator><creator>Hora, S.C.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T2</scope><scope>7U2</scope><scope>C1K</scope></search><sort><creationdate>20080701</creationdate><title>Extension of Latin hypercube samples with correlated variables</title><author>Sallaberry, C.J. ; Helton, J.C. ; Hora, S.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c405t-6403f7f6912743aef325abf76c4959f12113e73016dc9be72448bb6bacef29503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Applied sciences</topic><topic>Exact sciences and technology</topic><topic>Experimental design</topic><topic>Latin hypercube sample</topic><topic>Mathematics</topic><topic>Monte Carlo analysis</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Probability and statistics</topic><topic>Rank correlation</topic><topic>Reliability theory. Replacement problems</topic><topic>Sample size extension</topic><topic>Sciences and techniques of general use</topic><topic>Sensitivity analysis</topic><topic>Statistics</topic><topic>Uncertainty analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sallaberry, C.J.</creatorcontrib><creatorcontrib>Helton, J.C.</creatorcontrib><creatorcontrib>Hora, S.C.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Safety Science and Risk</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Reliability engineering & system safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sallaberry, C.J.</au><au>Helton, J.C.</au><au>Hora, S.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Extension of Latin hypercube samples with correlated variables</atitle><jtitle>Reliability engineering & system safety</jtitle><date>2008-07-01</date><risdate>2008</risdate><volume>93</volume><issue>7</issue><spage>1047</spage><epage>1059</epage><pages>1047-1059</pages><issn>0951-8320</issn><eissn>1879-0836</eissn><abstract>A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size
m and associated rank correlation matrix
C and constructs a new LHS of size 2
m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix
C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ress.2007.04.005</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0951-8320 |
| ispartof | Reliability engineering & system safety, 2008-07, Vol.93 (7), p.1047-1059 |
| issn | 0951-8320 1879-0836 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_19629919 |
| source | ScienceDirect Journals (5 years ago - present) |
| subjects | Applied sciences Exact sciences and technology Experimental design Latin hypercube sample Mathematics Monte Carlo analysis Operational research and scientific management Operational research. Management science Probability and statistics Rank correlation Reliability theory. Replacement problems Sample size extension Sciences and techniques of general use Sensitivity analysis Statistics Uncertainty analysis |
| title | Extension of Latin hypercube samples with correlated variables |
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