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Libri sul tema "Bayesian modelling"

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Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 11 marzo 2023

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1

Congdon, Peter. Applied Bayesian Modelling. Chichester, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118895047.

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2

Bayesian statistical modelling. 2^a ed. Chichester, England: John Wiley & Sons, 2006.

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3

Shevchenko, Pavel V. Modelling Operational Risk Using Bayesian Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-15923-7.

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4

Modelling Operational Risk Using Bayesian Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.

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5

Stübler, Sabine. Modelling Proteasome Dynamics in a Bayesian Framework. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-20167-8.

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6

Alston, Clair L., Kerrie L. Mengersen e Anthony N. Pettitt, a cura di. Case Studies in Bayesian Statistical Modelling and Analysis. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118394472.

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7

Hans, Bandemer, a cura di. Modelling uncertain data. Berlin: Akademie Verlag, 1992.

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8

1957-, Clark James Samuel, e Gelfand Alan E. 1945-, a cura di. Hierarchical modelling for the environmental sciences: Statistical methods and applications. Oxford: Oxford University Press, 2006.

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9

Frontis Workshop on Bayesian Statistics and Quality Modelling in the Agro-food Production Chain (2003 Wageningen, Netherlands). Bayesian statistics and quality modelling in the agro-food production chain: Proceedings of the Frontis Workshop on Bayesian Statistics and Quality Modelling in the Agro-food Production Chain, Wageningen, The Netherlands, 11-14 May 2003. Boston: Kluwer Academic, 2004.

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10

Martikainen, Janne. Application of decision-analytic modelling in health economic evaluations. Kuopio: University of Kuopio, 2008.

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11

Congdon, Peter. Applied Bayesian Modelling. Wiley & Sons, Incorporated, John, 2003.

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12

Applied Bayesian Modelling. John Wiley & Sons Inc, 2014.

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13

Applied Bayesian Modelling. Wiley, 2003.

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14

Bayesian Statistical Modelling. Wiley, 2001.

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15

Congdon, Peter. Bayesian Statistical Modelling. Wiley & Sons, Incorporated, John, 2007.

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16

Congdon, Peter. Applied Bayesian Modelling. Wiley & Sons, Limited, John, 2014.

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17

Congdon, Peter. Applied Bayesian Modelling. Wiley & Sons, Incorporated, John, 2014.

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18

Congdon, Peter. Bayesian Statistical Modelling. Wiley, 2007.

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19

Congdon, Peter. Bayesian Statistical Modelling. Wiley & Sons, Incorporated, John, 2007.

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20

Congdon, Peter. Applied Bayesian Modelling. Wiley & Sons, Incorporated, John, 2014.

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21

Congdon, Peter. Bayesian Statistical Modelling. 2^a ed. John Wiley & Sons Inc, 2006.

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22

Congdon, P., e Peter Congdon. Applied Bayesian Modelling. Wiley & Sons, Incorporated, John, 2003.

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23

Congdon, Peter. Applied Bayesian Modelling. Wiley & Sons, Incorporated, John, 2014.

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24

Congdon, Peter. Applied Bayesian Modelling. Wiley & Sons, Incorporated, John, 2007.

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25

Flexible Bayesian Regression Modelling. Elsevier, 2020. http://dx.doi.org/10.1016/c2017-0-02121-3.

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26

Nott, David, Mike Smith, Yanan Fan e Jean-Luc Dortet-Bernadet. Flexible Bayesian Regression Modelling. Elsevier Science & Technology Books, 2019.

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27

Lucy, David, e James Michael Curran. Applied Bayesian Modelling with Jags. Taylor & Francis Group, 2022.

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28

Ferreira, Marco, Adelmo Bertoldey e Scott Holan. Bayesian modelling of train door reliability. A cura di Anthony O'Hagan e Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.11.

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Abstract (sommario):

This article discusses the results of a study in Bayesian reliability analysis concerning train door failures in a European underground system over a period of nine years. It examines failure data from forty underground trains, which were delivered to an European transportation company between November 1989 and March 1991. All of the trains were put in service from 20 March 1990 to 20 July 1992. Failure monitoring ended on 31 December 1998. The goal of the study was to find models able to assess the failure history and to predict the number of failures in future time intervals in order to help the company determine the reliability level of the train doors before warranty expiration. The article describes the development and application of a novel bivariate Poisson process as a natural way to extend the usual Poisson models for analysing the occurrence of failures in repairable systems.

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29

Modelling Operational Risk Using Bayesian Inference. Springer, 2011.

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30

Shevchenko, Pavel V. Modelling Operational Risk Using Bayesian Inference. Springer, 2014.

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31

Shevchenko, Pavel V. Modelling Operational Risk Using Bayesian Inference. Springer, 2011.

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32

Fernández-Villaverde, Jesús, Pablo Guerrón-Quintana e Juan Rubio-Ramírez. Futures markets, Bayesian forecasting and risk modelling. A cura di Anthony O'Hagan e Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.14.

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This article demonstrates the utility of the Bayesian approach in forecasting and risk modelling regarding speculative trading strategies in financial futures markets. It first provides an overview of subjective expectations that are motivated as fair prices of futures contracts before discussing the futures markets and a portfolio mean-variance efficiency generalization. In particular, it considers the critical role of hedging to ensue attractive risk-adjusted performance. It also describes general Bayesian dynamic models and specific Bayesian dynamic linear models for assessing risk models in terms of their hedging effectiveness in the context of the risk-adjusted performance of trading strategies. The article showcases applied Bayesian thinking in the context of financial investment management, highlighting the corresponding concepts of betting and investing, prices and expectations, and coherence and arbitrage-free pricing in futures markets over the period 1990–2008.

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33

Li, Yongjie, Ka-Veng Yuen, Ka In Hoi e Kai Meng Mok. Air Quality Monitoring and Advanced Bayesian Modelling. Elsevier, 2023.

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34

Stübler, Sabine. Modelling Proteasome Dynamics in a Bayesian Framework. Springer Spektrum, 2017.

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35

Li, Yongjie, Ka-Veng Yuen, Ka In Hoi e Kai Meng Mok. Air Quality Monitoring and Advanced Bayesian Modelling. Elsevier, 2023.

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36

Zellner, Arnold, Jack C. Lee e Wesley O. Johnson. Modelling and Prediction Honoring Seymour Geisser. Springer London, Limited, 2013.

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37

Zellner, Arnold, Jack C. Lee e Wesley O. Johnson. Modelling and Prediction Honoring Seymour Geisser. Springer, 2012.

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38

Green, Peter, Kanti Mardia, Vysaul Nyirongo e Yann Ruffieux. Bayesian modelling for matching and alignment of biomolecules. A cura di Anthony O'Hagan e Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.2.

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This article describes Bayesian modelling for matching and alignment of biomolecules. One particular task where statistical modelling and inference can be useful in scientific understanding of protein structure is that of matching and alignment of two or more proteins. In this regard, statistical shape analysis potentially has something to offer in solving biomolecule matching and alignment problems. The article discusses the use of Bayesian methods for shape analysis to assist with understanding the three-dimensional structure of protein molecules, with a focus on the problem of matching instances of the same structure in the CoMFA (Comparative Molecular Field Analysis) database of steroid molecules. It introduces a Bayesian hierarchical model for pairwise matching and for alignment of multiple configurations before concluding with an overview of some advantages of the Bayesian approach to problems in protein bioinformatics, along with modelling and computation issues, alternative approaches, and directions for future research.

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39

Sahu, Sujit Kumar. Bayesian Modelling of Spatio-Temporal Data with R. Taylor & Francis Group, 2022.

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40

Case Studies In Bayesian Statistical Modelling And Analysis. John Wiley & Sons, 2012.

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41

Mengersen, Kerrie L., Clair L. Alston e Anthony N. Pettitt. Case Studies in Bayesian Statistical Modelling and Analysis. Wiley & Sons, Incorporated, John, 2012.

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42

Mengersen, Kerrie L., Clair L. Alston e Anthony N. Pettitt. Case Studies in Bayesian Statistical Modelling and Analysis. Wiley & Sons, Incorporated, John, 2012.

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43

Karolyi, G. Andrew. A Bayesian approach to modelling stock return volatility. 1989.

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44

Sahu, Sujit Kumar. Bayesian Modelling of Spatio-Temporal Data with R. Taylor & Francis Group, 2022.

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45

Sahu, Sujit Kumar. Bayesian Modelling of Spatio-Temporal Data with R. Taylor & Francis Group, 2022.

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46

Mengersen, Kerrie L., Clair L. Alston e Anthony N. Pettitt. Case Studies in Bayesian Statistical Modelling and Analysis. Wiley & Sons, Incorporated, John, 2012.

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47

Bayesian Modelling of Spatio-Temporal Data with R. Taylor & Francis Group, 2022.

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48

Mengersen, Kerrie L., Clair L. Alston e Anthony N. Pettitt. Case Studies in Bayesian Statistical Modelling and Analysis. Wiley & Sons, Incorporated, John, 2012.

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49

Mengersen, Kerrie L., Clair L. Alston e Anthony N. Pettitt. Case Studies in Bayesian Statistical Modelling and Analysis. Wiley & Sons, Incorporated, John, 2012.

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50

(Editor), Jack C. Lee, Wesley O. Johnson (Editor) e Arnold Zellner (Editor), a cura di. Modelling and Prediction: Honoring Seymour Geisser. Springer, 1996.

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