MOST ROBUST BIBDs
Since the time of Fisher and Yates, intense combinatorial study of balanced incomplete block designs has led to a great many designs with the same numbers of treatments, blocks, and block size. While the basic analysis does not differentiate among different BIBDs with the same parameters, they do di...
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Veröffentlicht in: | Statistica Sinica 2008-04, Vol.18 (2), p.689-707 |
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description | Since the time of Fisher and Yates, intense combinatorial study of balanced incomplete block designs has led to a great many designs with the same numbers of treatments, blocks, and block size. While the basic analysis does not differentiate among different BIBDs with the same parameters, they do differ in their capacity to withstand loss of experimental material. Competing BIBDs are compared here for their robustness in terms of average loss and worst loss. A table of most robust BIBDs is compiled. Two useful criteria are minimum intersection aberration and minimum efficiency aberration. |
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While the basic analysis does not differentiate among different BIBDs with the same parameters, they do differ in their capacity to withstand loss of experimental material. Competing BIBDs are compared here for their robustness in terms of average loss and worst loss. A table of most robust BIBDs is compiled. Two useful criteria are minimum intersection aberration and minimum efficiency aberration.</description><subject>Arithmetic mean</subject><subject>Design efficiency</subject><subject>Eigenvalues</subject><subject>Experiment design</subject><subject>Information economics</subject><subject>Mathematical robustness</subject><subject>Matrices</subject><subject>Missing data</subject><subject>Statistical discrepancies</subject><subject>Statistical variance</subject><issn>1017-0405</issn><issn>1996-8507</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNotzk0KwjAUBOAgChZ14QEELxB4yUubZGnrX0EpaLuWJm3AoihNN97egK6-Wc3MiERM64SqGOQ4ZGCSgoB4Shbe3w2AhpgpwIgsz8W1XF-KtAqkebr1czJx9cO3i78zUu13ZXakp-KQZ5sT7ZiUA61dg4m2inEeFMaCZdqBQRnWmOPMtkJog4BtqxqbaK6dcgZQ1olpLMcZWf16Oz-8-tu7vz_r_nPjAiHc5vgFX2Mxbg</recordid><startdate>20080401</startdate><enddate>20080401</enddate><creator>Morgan, John P.</creator><creator>Parvu, Valentin</creator><general>Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association</general><scope/></search><sort><creationdate>20080401</creationdate><title>MOST ROBUST BIBDs</title><author>Morgan, John P. ; Parvu, Valentin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j177t-afd369c81223694bc0c19f0b371011f21ce449b303ee8dc6929f8fb037a6bdc23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Arithmetic mean</topic><topic>Design efficiency</topic><topic>Eigenvalues</topic><topic>Experiment design</topic><topic>Information economics</topic><topic>Mathematical robustness</topic><topic>Matrices</topic><topic>Missing data</topic><topic>Statistical discrepancies</topic><topic>Statistical variance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Morgan, John P.</creatorcontrib><creatorcontrib>Parvu, Valentin</creatorcontrib><jtitle>Statistica Sinica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Morgan, John P.</au><au>Parvu, Valentin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MOST ROBUST BIBDs</atitle><jtitle>Statistica Sinica</jtitle><date>2008-04-01</date><risdate>2008</risdate><volume>18</volume><issue>2</issue><spage>689</spage><epage>707</epage><pages>689-707</pages><issn>1017-0405</issn><eissn>1996-8507</eissn><abstract>Since the time of Fisher and Yates, intense combinatorial study of balanced incomplete block designs has led to a great many designs with the same numbers of treatments, blocks, and block size. While the basic analysis does not differentiate among different BIBDs with the same parameters, they do differ in their capacity to withstand loss of experimental material. Competing BIBDs are compared here for their robustness in terms of average loss and worst loss. A table of most robust BIBDs is compiled. Two useful criteria are minimum intersection aberration and minimum efficiency aberration.</abstract><pub>Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association</pub><tpages>19</tpages></addata></record> |
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issn | 1017-0405 1996-8507 |
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source | JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; EZB-FREE-00999 freely available EZB journals |
subjects | Arithmetic mean Design efficiency Eigenvalues Experiment design Information economics Mathematical robustness Matrices Missing data Statistical discrepancies Statistical variance |
title | MOST ROBUST BIBDs |
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