Results 21 to 30 of about 157,640 (328)
A hierarchical Bayesian model for frame representation [PDF]
2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010 In many signal processing problems, it may be fruitful to represent the signal under study in a frame. If a probabilistic approach is adopted, it becomes then necessary to estimate the hyper-parameters characterizing the probability distribution of the frame coefficients.
Chaari, Lotfi +4 more
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Bayesian hierarchical linear modeling of NFL quarterback rating [PDF]
, 2015 textWith endless amounts of statistics in American football, there are numerous ways to evaluate quarterback performance in the National Football League.
Hernandez, Steven V.
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Hierarchical Bayesian Reliability Model for Wind Turbines with Small Fault Sample Sets
Zhongguo dianli, 2019 It is beneficial to improve the health management level of the full-life-cycle of wind turbines through establishing the reliability model for wind turbine and estimating its parameter accurately. As the fault sample size of new constructed wind turbines
Dameng WANG +3 more
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User-friendly Bayesian regression modeling: A tutorial with rstanarm and shinystan [PDF]
Tutorials in Quantitative Methods for Psychology, 2018 This tutorial provides a pragmatic introduction to specifying, estimating and interpreting single-level and hierarchical linear regression models in the Bayesian framework. We start by summarizing why one should consider the Bayesian approach to the most
Muth, Chelsea +2 more
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Hierarchical Bayesian Modeling of Hitting Performance in Baseball [PDF]
, 2009 We have developed a sophisticated statistical model for predicting the hitting performance of Major League baseball players. The Bayesian paradigm provides a principled method for balancing past performance with crucial covariates, such as player age and
Jensen, Shane T. +2 more
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Modelling unexpected failures with a hierarchical Bayesian model [PDF]
2017 2nd International Conference on System Reliability and Safety (ICSRS), 2017 Systems, especially those in the design and development phase, frequently suffer from unexpected failures, which are caused by insufficient knowledge of the system failure processes. In this paper, we develop a hierarchical Bayesian reliability model that account for unexpected failures.
Zeng, Zhiguo, Zio, Enrico
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Modeling Topic and Role Information in Meetings using the Hierarchical Dirichlet Process [PDF]
, 2008 . In this paper, we address the modeling of topic and role information in multiparty meetings, via a nonparametric Bayesian model called the hierarchical Dirichlet process.
Huang, Songfang, Renals, Steve
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BVAR: Bayesian Vector Autoregressions with Hierarchical Prior Selection in R
Journal of Statistical Software, 2021 Vector autoregression (VAR) models are widely used for multivariate time series analysis in macroeconomics, finance, and related fields. Bayesian methods are often employed to deal with their dense parameterization, imposing structure on model ...
Nikolas Kuschnig, Lukas Vashold
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Analyzing Postdisaster Surveillance Data: The Effect of the Statistical Method [PDF]
, 2008 Data from existing administrative databases and ongoing surveys or surveillance methods may prove indispensable after mass traumas as a way of providing information that may be useful to emergency planners and practitioners.
DiMaggio, Charles J. +2 more
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A Bayesian hierarchical model for allele frequencies [PDF]
Genetic Epidemiology, 2000 Genetic epidemiological methodologies, such as linkage analysis, often require accurate estimates of allele frequencies. When studies involve multiple sub-populations with different evolutionary histories, accurate estimates can be difficult to obtain because the number of subjects per sub-population tends to be limited.
J R, Lockwood, K, Roeder, B, Devlin
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