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  • Search: subject:"Generalized confidence intervals"
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Year of publication
Subject
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Generalized confidence intervals 3 generalized confidence intervals 2 negotiation process 2 Confidence distributions 1 Confidence intervals 1 Control variates 1 Coverage probability 1 Dempster–Shafer calculus 1 Fiducial quantity 1 Generalized confidence intervals (GCI) 1 Generalized fiducial inference 1 Generalized pivotal quantities 1 Intraclass correlation coefficient 1 Lognormal distribution 1 Lower confidence limits 1 Modified large sample (MLS) 1 Process capability index 1 Rao-Blackwellization 1 Sample size 1 Variance components 1 bodily injury claims compensation 1 multivariate statistics 1
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Online availability
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Undetermined 4 Free 1
Type of publication
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Article 4 Book / Working Paper 2
Language
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Undetermined 5 English 1
Author
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Ayuso, Mercedes 2 Santolino, Miguel 2 Dobbin, Kevin K. 1 Hannig, Jan 1 Hsu, Bi-Min 1 Ionan, Alexei C. 1 Lai, Randy C.S. 1 Lee, Thomas C.M. 1 Li, Xinmin 1 Shu, Ming-Hung 1 Tian, Lili 1 Wu, Chien-Wei 1 Zhou, Xiaohua 1
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Institution
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Facultat d'Economia i Empresa, Universitat de Barcelona 2
Published in...
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Computational Statistics & Data Analysis 2 IREA Working Papers 1 Metrika 1 Statistics & Probability Letters 1 Working Papers in Economics 1
Source
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RePEc 6
Showing 1 - 6 of 6
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Sample size methods for constructing confidence intervals for the intra-class correlation coefficient
Dobbin, Kevin K.; Ionan, Alexei C. - In: Computational Statistics & Data Analysis 85 (2015) C, pp. 67-83
The intraclass correlation coefficient (ICC) in a two-way analysis of variance is a ratio involving three variance components. Two recently developed methods for constructing confidence intervals (CI’s) for the ICC are the Generalized Confidence Interval (GCI) and Modified Large Sample (MLS)...
Persistent link: https://www.econbiz.de/10011191017
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Forecasting the maximum compensation offer in the automobile BI claims negotiation proces.
Ayuso, Mercedes; Santolino, Miguel - Facultat d'Economia i Empresa, Universitat de Barcelona - 2008
Most motor bodily injury (BI) claims are settled by negotiation, with fewer than 5% of cases going to court. A well-defined negotiation strategy is thus very useful for insurance companies. In this paper we assume that the monetary compensation awarded in court is the upper amount to be offered...
Persistent link: https://www.econbiz.de/10005059593
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Computational issues of generalized fiducial inference
Hannig, Jan; Lai, Randy C.S.; Lee, Thomas C.M. - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 849-858
Generalized fiducial inference is closely related to the Dempster–Shafer theory of belief functions. It is a general methodology for constructing a distribution on a (possibly vector-valued) model parameter without the use of any prior distribution. The resulting distribution is called the...
Persistent link: https://www.econbiz.de/10010871372
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Interval estimation for the mean of lognormal data with excess zeros
Li, Xinmin; Zhou, Xiaohua; Tian, Lili - In: Statistics & Probability Letters 83 (2013) 11, pp. 2447-2453
This paper considered interval estimations for the mean of lognormal distribution with excess zeros. We proposed two methods for interval estimation based on an approximate generalized pivotal quantity and a fiducial quantity. Simulation results show that the fiducial approach has highly...
Persistent link: https://www.econbiz.de/10010709058
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Individual prediction of automobile bodily injury claims liabilities
Ayuso, Mercedes; Santolino, Miguel - Facultat d'Economia i Empresa, Universitat de Barcelona - 2009
Most motor bodily injury (BI) claims are settled by negotiation, with fewer than 5% of cases going to court. A well-defined negotiation strategy is thus very useful for insurance companies. In this paper we assume that the monetary compensation awarded in court is the upper amount to be offered...
Persistent link: https://www.econbiz.de/10005022337
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Generalized confidence intervals for the process capability index C <Subscript>pm</Subscript>
Hsu, Bi-Min; Wu, Chien-Wei; Shu, Ming-Hung - In: Metrika 68 (2008) 1, pp. 65-82
Persistent link: https://www.econbiz.de/10005375757
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