Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity

Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis us...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Mathews, K. A. [verfasserIn] Gerts, D. W.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2008

Schlagwörter:	BAYESIAN Analysis False Detection Decision Level Background Count Background Measurement

Anmerkung:	© Springer Science+Business Media, LLC. 2007

Übergeordnetes Werk:	Enthalten in: Journal of radioanalytical and nuclear chemistry - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1968, 276(2008), 2 vom: Mai, Seite 305-312
Übergeordnetes Werk:	volume:276 ; year:2008 ; number:2 ; month:05 ; pages:305-312

Links:	Volltext

DOI / URN:	10.1007/s10967-008-0503-3

Katalog-ID:	SPR015156826

Internformat


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520			\|a Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions.
650		4	\|a BAYESIAN Analysis \|7 (dpeaa)DE-He213
650		4	\|a False Detection \|7 (dpeaa)DE-He213
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650		4	\|a Background Count \|7 (dpeaa)DE-He213
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912			\|a GBV_ILN_63
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
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912			\|a GBV_ILN_101
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2070
912			\|a GBV_ILN_2086
912			\|a GBV_ILN_2088
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912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2116
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2119
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2188
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
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912			\|a GBV_ILN_4333
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912			\|a GBV_ILN_4336
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allfields	10.1007/s10967-008-0503-3 doi (DE-627)SPR015156826 (SPR)s10967-008-0503-3-e DE-627 ger DE-627 rakwb eng Mathews, K. A. verfasserin aut Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC. 2007 Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. BAYESIAN Analysis (dpeaa)DE-He213 False Detection (dpeaa)DE-He213 Decision Level (dpeaa)DE-He213 Background Count (dpeaa)DE-He213 Background Measurement (dpeaa)DE-He213 Gerts, D. W. aut Enthalten in Journal of radioanalytical and nuclear chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1968 276(2008), 2 vom: Mai, Seite 305-312 (DE-627)320578011 (DE-600)2017242-4 1588-2780 nnns volume:276 year:2008 number:2 month:05 pages:305-312 https://dx.doi.org/10.1007/s10967-008-0503-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 276 2008 2 05 305-312
spelling	10.1007/s10967-008-0503-3 doi (DE-627)SPR015156826 (SPR)s10967-008-0503-3-e DE-627 ger DE-627 rakwb eng Mathews, K. A. verfasserin aut Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC. 2007 Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. BAYESIAN Analysis (dpeaa)DE-He213 False Detection (dpeaa)DE-He213 Decision Level (dpeaa)DE-He213 Background Count (dpeaa)DE-He213 Background Measurement (dpeaa)DE-He213 Gerts, D. W. aut Enthalten in Journal of radioanalytical and nuclear chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1968 276(2008), 2 vom: Mai, Seite 305-312 (DE-627)320578011 (DE-600)2017242-4 1588-2780 nnns volume:276 year:2008 number:2 month:05 pages:305-312 https://dx.doi.org/10.1007/s10967-008-0503-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 276 2008 2 05 305-312
allfields_unstemmed	10.1007/s10967-008-0503-3 doi (DE-627)SPR015156826 (SPR)s10967-008-0503-3-e DE-627 ger DE-627 rakwb eng Mathews, K. A. verfasserin aut Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC. 2007 Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. BAYESIAN Analysis (dpeaa)DE-He213 False Detection (dpeaa)DE-He213 Decision Level (dpeaa)DE-He213 Background Count (dpeaa)DE-He213 Background Measurement (dpeaa)DE-He213 Gerts, D. W. aut Enthalten in Journal of radioanalytical and nuclear chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1968 276(2008), 2 vom: Mai, Seite 305-312 (DE-627)320578011 (DE-600)2017242-4 1588-2780 nnns volume:276 year:2008 number:2 month:05 pages:305-312 https://dx.doi.org/10.1007/s10967-008-0503-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 276 2008 2 05 305-312
allfieldsGer	10.1007/s10967-008-0503-3 doi (DE-627)SPR015156826 (SPR)s10967-008-0503-3-e DE-627 ger DE-627 rakwb eng Mathews, K. A. verfasserin aut Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC. 2007 Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. BAYESIAN Analysis (dpeaa)DE-He213 False Detection (dpeaa)DE-He213 Decision Level (dpeaa)DE-He213 Background Count (dpeaa)DE-He213 Background Measurement (dpeaa)DE-He213 Gerts, D. W. aut Enthalten in Journal of radioanalytical and nuclear chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1968 276(2008), 2 vom: Mai, Seite 305-312 (DE-627)320578011 (DE-600)2017242-4 1588-2780 nnns volume:276 year:2008 number:2 month:05 pages:305-312 https://dx.doi.org/10.1007/s10967-008-0503-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 276 2008 2 05 305-312
allfieldsSound	10.1007/s10967-008-0503-3 doi (DE-627)SPR015156826 (SPR)s10967-008-0503-3-e DE-627 ger DE-627 rakwb eng Mathews, K. A. verfasserin aut Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity 2008 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC. 2007 Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. BAYESIAN Analysis (dpeaa)DE-He213 False Detection (dpeaa)DE-He213 Decision Level (dpeaa)DE-He213 Background Count (dpeaa)DE-He213 Background Measurement (dpeaa)DE-He213 Gerts, D. W. aut Enthalten in Journal of radioanalytical and nuclear chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1968 276(2008), 2 vom: Mai, Seite 305-312 (DE-627)320578011 (DE-600)2017242-4 1588-2780 nnns volume:276 year:2008 number:2 month:05 pages:305-312 https://dx.doi.org/10.1007/s10967-008-0503-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 276 2008 2 05 305-312
language	English
source	Enthalten in Journal of radioanalytical and nuclear chemistry 276(2008), 2 vom: Mai, Seite 305-312 volume:276 year:2008 number:2 month:05 pages:305-312
sourceStr	Enthalten in Journal of radioanalytical and nuclear chemistry 276(2008), 2 vom: Mai, Seite 305-312 volume:276 year:2008 number:2 month:05 pages:305-312
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	BAYESIAN Analysis False Detection Decision Level Background Count Background Measurement
isfreeaccess_bool	false
container_title	Journal of radioanalytical and nuclear chemistry
authorswithroles_txt_mv	Mathews, K. A. @@aut@@ Gerts, D. W. @@aut@@
publishDateDaySort_date	2008-05-01T00:00:00Z
hierarchy_top_id	320578011
id	SPR015156826
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author	Mathews, K. A.
spellingShingle	Mathews, K. A. misc BAYESIAN Analysis misc False Detection misc Decision Level misc Background Count misc Background Measurement Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity
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topic_title	Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity BAYESIAN Analysis (dpeaa)DE-He213 False Detection (dpeaa)DE-He213 Decision Level (dpeaa)DE-He213 Background Count (dpeaa)DE-He213 Background Measurement (dpeaa)DE-He213
topic	misc BAYESIAN Analysis misc False Detection misc Decision Level misc Background Count misc Background Measurement
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title	Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity
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title_full	Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity
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title_sort	bayesian analysis for very-low-background counting of short-lived isotopes: lowest minimum detectable quantity
title_auth	Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity
abstract	Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. © Springer Science+Business Media, LLC. 2007
abstractGer	Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. © Springer Science+Business Media, LLC. 2007
abstract_unstemmed	Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. An alternative is presented here: Bayesian analysis using longer-duration background measurements, appropriate modeling of the background, and a binomial distribution of decay-induced counts valid even for short-lived isotopes. We develop the needed formulae and demonstrate how the decision level and sample measurement duration are optimized jointly to produce the lowest minimum detectable quantity subject to constraints of specified acceptable risks of false detection and false failure to detect. A frequentist’s interpretation is maintained by using equal-likelihood prior distributions. © Springer Science+Business Media, LLC. 2007
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title_short	Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity
url	https://dx.doi.org/10.1007/s10967-008-0503-3
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up_date	2024-07-03T14:17:54.328Z
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A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2008</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">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC. 2007</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Conventional statistical analyses of counting measurements with a paired-count blank and sample yield unacceptably-large estimates of uncertainty that reduce measurement sensitivity when applied to very-low-background detection systems. 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Bayesian analysis for very-low-background counting of short-lived isotopes: Lowest minimum detectable quantity

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