Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples
This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for de...
Ausführliche Beschreibung
Autor*in: |
Jovanović, Milan [verfasserIn] |
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Sprache: |
Englisch |
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2015 |
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Enthalten in: Communications in statistics / Simulation and computation - New York, NY : Dekker, 1982, 46(2015), 4, Seite 1-17 |
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Übergeordnetes Werk: |
volume:46 ; year:2015 ; number:4 ; pages:1-17 |
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DOI / URN: |
10.1080/03610918.2015.1073302 |
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OLC1992784248 |
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10.1080/03610918.2015.1073302 doi PQ20170501 (DE-627)OLC1992784248 (DE-599)GBVOLC1992784248 (PRQ)c1271-17fdfb1c6694cc58f0e105a20cdd0671b1bb18bc16e4412e6252a748ac7a20d10 (KEY)0108850520150000046000400001estimationofpxyforgeometricexponentialmodelbasedon DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Jovanović, Milan verfasserin aut Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. Economic models Random variables Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 46(2015), 4, Seite 1-17 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:46 year:2015 number:4 pages:1-17 http://dx.doi.org/10.1080/03610918.2015.1073302 Volltext http://search.proquest.com/docview/1891842031 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 46 2015 4 1-17 |
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10.1080/03610918.2015.1073302 doi PQ20170501 (DE-627)OLC1992784248 (DE-599)GBVOLC1992784248 (PRQ)c1271-17fdfb1c6694cc58f0e105a20cdd0671b1bb18bc16e4412e6252a748ac7a20d10 (KEY)0108850520150000046000400001estimationofpxyforgeometricexponentialmodelbasedon DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Jovanović, Milan verfasserin aut Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. Economic models Random variables Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 46(2015), 4, Seite 1-17 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:46 year:2015 number:4 pages:1-17 http://dx.doi.org/10.1080/03610918.2015.1073302 Volltext http://search.proquest.com/docview/1891842031 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 46 2015 4 1-17 |
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10.1080/03610918.2015.1073302 doi PQ20170501 (DE-627)OLC1992784248 (DE-599)GBVOLC1992784248 (PRQ)c1271-17fdfb1c6694cc58f0e105a20cdd0671b1bb18bc16e4412e6252a748ac7a20d10 (KEY)0108850520150000046000400001estimationofpxyforgeometricexponentialmodelbasedon DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Jovanović, Milan verfasserin aut Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. Economic models Random variables Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 46(2015), 4, Seite 1-17 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:46 year:2015 number:4 pages:1-17 http://dx.doi.org/10.1080/03610918.2015.1073302 Volltext http://search.proquest.com/docview/1891842031 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 46 2015 4 1-17 |
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10.1080/03610918.2015.1073302 doi PQ20170501 (DE-627)OLC1992784248 (DE-599)GBVOLC1992784248 (PRQ)c1271-17fdfb1c6694cc58f0e105a20cdd0671b1bb18bc16e4412e6252a748ac7a20d10 (KEY)0108850520150000046000400001estimationofpxyforgeometricexponentialmodelbasedon DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Jovanović, Milan verfasserin aut Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. Economic models Random variables Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 46(2015), 4, Seite 1-17 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:46 year:2015 number:4 pages:1-17 http://dx.doi.org/10.1080/03610918.2015.1073302 Volltext http://search.proquest.com/docview/1891842031 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 46 2015 4 1-17 |
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10.1080/03610918.2015.1073302 doi PQ20170501 (DE-627)OLC1992784248 (DE-599)GBVOLC1992784248 (PRQ)c1271-17fdfb1c6694cc58f0e105a20cdd0671b1bb18bc16e4412e6252a748ac7a20d10 (KEY)0108850520150000046000400001estimationofpxyforgeometricexponentialmodelbasedon DE-627 ger DE-627 rakwb eng 510 DE-600 31.73 bkl Jovanović, Milan verfasserin aut Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. Economic models Random variables Enthalten in Communications in statistics / Simulation and computation New York, NY : Dekker, 1982 46(2015), 4, Seite 1-17 (DE-627)129862258 (DE-600)283664-6 (DE-576)015173682 0361-0918 nnns volume:46 year:2015 number:4 pages:1-17 http://dx.doi.org/10.1080/03610918.2015.1073302 Volltext http://search.proquest.com/docview/1891842031 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 31.73 AVZ AR 46 2015 4 1-17 |
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Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples |
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This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. |
abstractGer |
This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. |
abstract_unstemmed |
This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained. |
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Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1992784248</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220219163335.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">170512s2015 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1080/03610918.2015.1073302</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20170501</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1992784248</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1992784248</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1271-17fdfb1c6694cc58f0e105a20cdd0671b1bb18bc16e4412e6252a748ac7a20d10</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0108850520150000046000400001estimationofpxyforgeometricexponentialmodelbasedon</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.73</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jovanović, Milan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. 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