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An Uncoupling Coupling method for Markov chain Monte Carlo simulations with an application to biomoleculesFischer, Alexander. January 2003 (has links)
Berlin, Freie Universiẗat, Diss., 2003. / Dateiformat: zip, Dateien im PDF-Format.
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Bayesian analysis of the heterogeneity modelFrühwirth-Schnatter, Sylvia, Tüchler, Regina, Otter, Thomas January 2002 (has links) (PDF)
In the present paper we consider Bayesian estimation of a finite mixture of models with random effects which is also known as the heterogeneity model. First, we discuss the properties of various MCMC samplers that are obtained from full conditional Gibbs sampling by grouping and collapsing. Whereas full conditional Gibbs sampling turns out to be sensitive to the parameterization chosen for the mean structure of the model, the alternative sampler is robust in this respect. However, the logical extension of the approach to the sampling of the group variances does not further increase the efficiency of the sampler. Second, we deal with the identifiability problem due to the arbitrary labeling within the model. Finally, a case study involving metric Conjoint analysis serves as a practical illustration. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
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Hierarchical Bayesian spatial regression models with applications to non-life insuranceGschlössl, Susanne Unknown Date (has links) (PDF)
München, Techn. Univ., Diss., 2006
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Bayesian methods in portfolio credit risk managementWendin, Jonathan Erik Purvis. January 2006 (has links) (PDF)
Diss., Eidgenössische Technische Hochschule ETH Zürich, Nr. 16481, 2006.
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An Uncoupling Coupling method for Markov chain Monte Carlo simulations with an application to biomoleculesFischer, Alexander. Unknown Date (has links)
Freie Universiẗat, Diss., 2003--Berlin. / Dateiformat: zip, Dateien im PDF-Format.
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Simulation and validation of an integrated markets modelSallans, Brian, Pfister, Alexander, Karatzoglou, Alexandros, Dorffner, Georg January 2003 (has links) (PDF)
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model consists of heterogenous consumers, financial traders, and production firms. The production firms operate in the consumer market, and offer their shares to be traded on the financial market. The model is validated by comparing its output to known empirical properties of real markets. In order to better explore the influence of model parameters on behavior, a novel Markov chain Monte Carlo method is introduced. This method allows for the efficient exploration of large parameter spaces, in order to find which parameter regimes lead to reproduction of empirical phenomena. It is shown that the integrated markets model can reproduce a number of empirical "stylized facts", including learning-by-doing effects, fundamental price effects, low autocorrelations, volatility clustering, high kurtosis, and volatility-volume correlations. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
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Hierarchical binary spatial regression models with cluster effectsProkopenko, Sergiy. January 2004 (has links) (PDF)
München, Techn. Univ., Diss., 2004.
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Entwicklung eines Monte-Carlo-Verfahrens zum selbständigen Lernen von Gauß-MischverteilungenLauer, Martin. Unknown Date (has links) (PDF)
Universiẗat, Diss., 2004--Osnabrück.
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A Stochastic Model for the Process of LearningVoskoglou, Michael Gr. 11 May 2012 (has links) (PDF)
A Markov chain is introduced to the major steps of the process of learning a subject matter by a group of students in the classroom, in order to obtain a mathematical representation of the above process. A classroom experiment for learning mathematics is also presented illustrating the applicability of our results in practice.
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Mathematical modelling in classroom: The importance of validation of the constructed modelVoskoglou, Michael Gr. 20 March 2012 (has links) (PDF)
No description available.
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