Binary consecutive covering arrays
A k × n array with entries from a q -letter alphabet is called a t -covering array if each t × n submatrix contains amongst its columns each one of the q t different words of length t that can be produced by the q letters. In the present article we use a probabilistic approach based on an appropri...
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Veröffentlicht in: | Annals of the Institute of Statistical Mathematics 2011-06, Vol.63 (3), p.559-584 |
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container_title | Annals of the Institute of Statistical Mathematics |
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creator | Godbole, A. P. Koutras, M. V. Milienos, F. S. |
description | A
k
×
n
array with entries from a
q
-letter alphabet is called a
t
-covering array if each
t
×
n
submatrix contains amongst its columns each one of the
q
t
different words of length
t
that can be produced by the
q
letters. In the present article we use a probabilistic approach based on an appropriate Markov chain embedding technique, to study a
t
-covering problem where, instead of looking at all possible
t
×
n
submatrices, we consider only submatrices of dimension
t
×
n
with its rows being consecutive rows of the original
k
×
n
array. Moreover, an exact formula is established for the probability distribution function of the random variable, which enumerates the number of deficient submatrices (i.e., submatrices with at least one missing word, amongst their columns), in the case of a
k × n
binary matrix (
q
= 2) obtained by realizing
kn
Bernoulli variables. |
doi_str_mv | 10.1007/s10463-009-0240-6 |
format | Article |
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k
×
n
array with entries from a
q
-letter alphabet is called a
t
-covering array if each
t
×
n
submatrix contains amongst its columns each one of the
q
t
different words of length
t
that can be produced by the
q
letters. In the present article we use a probabilistic approach based on an appropriate Markov chain embedding technique, to study a
t
-covering problem where, instead of looking at all possible
t
×
n
submatrices, we consider only submatrices of dimension
t
×
n
with its rows being consecutive rows of the original
k
×
n
array. Moreover, an exact formula is established for the probability distribution function of the random variable, which enumerates the number of deficient submatrices (i.e., submatrices with at least one missing word, amongst their columns), in the case of a
k × n
binary matrix (
q
= 2) obtained by realizing
kn
Bernoulli variables.</description><identifier>ISSN: 0020-3157</identifier><identifier>EISSN: 1572-9052</identifier><identifier>DOI: 10.1007/s10463-009-0240-6</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Arrays ; Bernoulli Hypothesis ; Binary system ; Computers ; Covering ; Design of experiments ; Economics ; Finance ; Insurance ; Management ; Markov analysis ; Mathematical analysis ; Mathematical models ; Mathematics ; Mathematics and Statistics ; Operating systems ; Probabilistic methods ; Probability ; Probability distribution ; Probability distribution functions ; Probability theory ; Random variables ; Software ; Statistics ; Statistics for Business ; Studies</subject><ispartof>Annals of the Institute of Statistical Mathematics, 2011-06, Vol.63 (3), p.559-584</ispartof><rights>The Institute of Statistical Mathematics, Tokyo 2009</rights><rights>The Institute of Statistical Mathematics, Tokyo 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c373t-8a2e9d7b945105f9dc7f9866058e965a1ac9ad51d0c19b24e2ff7a14336f5fb73</citedby><cites>FETCH-LOGICAL-c373t-8a2e9d7b945105f9dc7f9866058e965a1ac9ad51d0c19b24e2ff7a14336f5fb73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10463-009-0240-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10463-009-0240-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Godbole, A. P.</creatorcontrib><creatorcontrib>Koutras, M. V.</creatorcontrib><creatorcontrib>Milienos, F. S.</creatorcontrib><title>Binary consecutive covering arrays</title><title>Annals of the Institute of Statistical Mathematics</title><addtitle>Ann Inst Stat Math</addtitle><description>A
k
×
n
array with entries from a
q
-letter alphabet is called a
t
-covering array if each
t
×
n
submatrix contains amongst its columns each one of the
q
t
different words of length
t
that can be produced by the
q
letters. In the present article we use a probabilistic approach based on an appropriate Markov chain embedding technique, to study a
t
-covering problem where, instead of looking at all possible
t
×
n
submatrices, we consider only submatrices of dimension
t
×
n
with its rows being consecutive rows of the original
k
×
n
array. Moreover, an exact formula is established for the probability distribution function of the random variable, which enumerates the number of deficient submatrices (i.e., submatrices with at least one missing word, amongst their columns), in the case of a
k × n
binary matrix (
q
= 2) obtained by realizing
kn
Bernoulli variables.</description><subject>Arrays</subject><subject>Bernoulli Hypothesis</subject><subject>Binary system</subject><subject>Computers</subject><subject>Covering</subject><subject>Design of experiments</subject><subject>Economics</subject><subject>Finance</subject><subject>Insurance</subject><subject>Management</subject><subject>Markov analysis</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Operating systems</subject><subject>Probabilistic methods</subject><subject>Probability</subject><subject>Probability distribution</subject><subject>Probability distribution functions</subject><subject>Probability theory</subject><subject>Random variables</subject><subject>Software</subject><subject>Statistics</subject><subject>Statistics for Business</subject><subject>Studies</subject><issn>0020-3157</issn><issn>1572-9052</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kE1LAzEQhoMoWKs_wFvpxVN08p0ctfgFBS96Dmk2kS3b3TXZLfTfm7KCIHiaYXjeYeZB6JrALQFQd5kAlwwDGAyUA5YnaEaEotiAoKdoBkABszI5Rxc5bwGAUUZnaPlQty4dFr5rc_DjUO9D6fch1e3nwqXkDvkSnUXX5HD1U-fo4-nxffWC12_Pr6v7NfZMsQFrR4Op1MZwQUBEU3kVjZYShA5GCkecN64SpAJPzIbyQGNUjnDGZBRxo9gc3Ux7-9R9jSEPdldnH5rGtaEbs9UaJNeC80Iu_5DbbkxtOc5qYQRQZUSByAT51OWcQrR9qnflV0vAHp3ZyZktzuzRmZUlQ6dM7o8CQvpd_H_oG5INbNQ</recordid><startdate>20110601</startdate><enddate>20110601</enddate><creator>Godbole, A. 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P. ; Koutras, M. V. ; Milienos, F. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c373t-8a2e9d7b945105f9dc7f9866058e965a1ac9ad51d0c19b24e2ff7a14336f5fb73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Arrays</topic><topic>Bernoulli Hypothesis</topic><topic>Binary system</topic><topic>Computers</topic><topic>Covering</topic><topic>Design of experiments</topic><topic>Economics</topic><topic>Finance</topic><topic>Insurance</topic><topic>Management</topic><topic>Markov analysis</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Operating systems</topic><topic>Probabilistic methods</topic><topic>Probability</topic><topic>Probability distribution</topic><topic>Probability distribution functions</topic><topic>Probability theory</topic><topic>Random variables</topic><topic>Software</topic><topic>Statistics</topic><topic>Statistics for Business</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Godbole, A. P.</creatorcontrib><creatorcontrib>Koutras, M. V.</creatorcontrib><creatorcontrib>Milienos, F. 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P.</au><au>Koutras, M. V.</au><au>Milienos, F. S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Binary consecutive covering arrays</atitle><jtitle>Annals of the Institute of Statistical Mathematics</jtitle><stitle>Ann Inst Stat Math</stitle><date>2011-06-01</date><risdate>2011</risdate><volume>63</volume><issue>3</issue><spage>559</spage><epage>584</epage><pages>559-584</pages><issn>0020-3157</issn><eissn>1572-9052</eissn><abstract>A
k
×
n
array with entries from a
q
-letter alphabet is called a
t
-covering array if each
t
×
n
submatrix contains amongst its columns each one of the
q
t
different words of length
t
that can be produced by the
q
letters. In the present article we use a probabilistic approach based on an appropriate Markov chain embedding technique, to study a
t
-covering problem where, instead of looking at all possible
t
×
n
submatrices, we consider only submatrices of dimension
t
×
n
with its rows being consecutive rows of the original
k
×
n
array. Moreover, an exact formula is established for the probability distribution function of the random variable, which enumerates the number of deficient submatrices (i.e., submatrices with at least one missing word, amongst their columns), in the case of a
k × n
binary matrix (
q
= 2) obtained by realizing
kn
Bernoulli variables.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s10463-009-0240-6</doi><tpages>26</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0020-3157 |
ispartof | Annals of the Institute of Statistical Mathematics, 2011-06, Vol.63 (3), p.559-584 |
issn | 0020-3157 1572-9052 |
language | eng |
recordid | cdi_proquest_miscellaneous_880648544 |
source | EZB-FREE-00999 freely available EZB journals; SpringerLink Journals - AutoHoldings |
subjects | Arrays Bernoulli Hypothesis Binary system Computers Covering Design of experiments Economics Finance Insurance Management Markov analysis Mathematical analysis Mathematical models Mathematics Mathematics and Statistics Operating systems Probabilistic methods Probability Probability distribution Probability distribution functions Probability theory Random variables Software Statistics Statistics for Business Studies |
title | Binary consecutive covering arrays |
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