Results 91 to 100 of about 23,661,782 (208)

Methods of a Priori Statistical Analysis of Disturbed Motion of Aircraft in Turbulent Environments

RUDN Journal of Engineering Research
The article discusses the methods of a priori statistical analysis used for predicting perturbed motion of aircraft in turbulent environments. Theoretical approaches such as the comparative method and mathematical modeling method are used to analyze the ...
Alexander S. Ermilov, Olga A. Saltykova
doaj   +1 more source

Honorary Lecture on S. James Press and Bayesian Analysis [PDF]

S. James Press's many contributions to statistical research, lecturing, mentoring students, the statistics profession, etc. are summarized. Then some new developments in Bayesian analysis are described and remarks on the future of Bayesian analysis are ...
Arnold Zellner
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Bayesian Stochastic Frontier Analysis Using WinBUGS [PDF]

Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This paper implements MCMC methods for Bayesian analysis of stochastic frontier models using the WinBUGS package, a freely available software.
Mark Steel, Jim Griffin
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Bayesian Analysis

, 2000
14 pages, 5 figures, Workshop on Confidence Limits, CERN, 17-18 January ...
openaire   +2 more sources

Bayesian Functional Data Analysis Using WinBUGS [PDF]

We provide user friendly software for Bayesian analysis of functional data models using \pkg{WinBUGS}~1.4. The excellent properties of Bayesian analysis in this context are due to: (1) dimensionality reduction, which leads to low dimensional projection ...
Ciprian M. Crainiceanu, A. Jeffrey Goldsmith   +1 more
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Bayesian Model Selection in the Analysis of Cointegration [PDF]

In this paper we present the Bayesian model selection procedure within the class of cointegrated processes. In order to make inference about the cointegration space we use the class of Matrix Angular Central Gaussian distributions. To carry out posterior
Justyna Wróblewska
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Bayesian Analysis of Non-normal and Non-independent Mixed Model UsingSkew-Normal/Independent Distributions

Journal of Biostatistics and Epidemiology, 2015
The  main  assumptions  in  liner  mixed  model  are normality  and  independency  of  random  effect component.   Unfortunately,   these   two  assumptions   might   be  unrealistic   in  some   situations.
Mohammad Gholami-Fesharaki, Anoshiravan Kazemnejad   +1 more
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A discussion of 'Sparse Bayesian factor analysis when the number of factors is unknown' by Sylvia Fruhwirth-Schnatter, Darjus Hosszejni and Hedibert Freitas Lopes

Conditional on knowing the number of factors, r, analysis in static and dynamic factor models is straightforward for the Bayesian. However, inference on r is challenging.
Koop, Gary, Hauzenberger, Niko
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Bayesian analysis. [PDF]

Journal of Epidemiology and Community Health, 1999
J Grossman, M K Parmar
openaire   +1 more source

Bayesian Analysis for Penalized Spline Regression Using WinBUGS [PDF]

Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression ...
Matthew P. Wand, David Ruppert, Ciprian M. Crainiceanu   +2 more
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