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Uncertainty analysis in matched-field geoacoustic inversions

Chen-Fen Huang, Peter Gerstoft, William S. Hodgkiss
2006 Journal of the Acoustical Society of America  
A full Bayesian approach that permits uncertainty of the error variance to propagate through the parameter estimation processes is a natural way of incorporating the uncertainty of error variance.  ...  Due to the large number of unknown parameters in the full Bayesian uncertainty analysis, an alternative, the empirical Bayesian approach, is developed, in which the posterior distributions of model parameters  ...  Full Bayesian estimation-numerical integration The full Bayesian approach is a natural way of incorporating the uncertainty of error variance in the analysis.  ... 
doi:10.1121/1.2139075 pmid:16454276 fatcat:cwddbzzr2fc7pj4qsarl2447ea

Bayesian analysis for genotype x environment interactions and the GGE-biplot assessment: Evaluation of balanced classifications with missing values

Siraj Osman Omer, Eltayeb Hassan Slafab, Abhishek Rathore
2015 International Journal of Applied Sciences and Biotechnology  
The authors thank Biometrics staff, ICRISAT for their help obtaining in statistical analysis.  ...  Acknowledgements This work was supported by CV Raman fellowship for Africa researchers grant in the India and by host institute International Crops Research Institute for the Semi-Arid Tropics (ICRISAT  ...  Two methods for heritability and genetic advance estimation were differing of both and among the three prior Bayesian approach in compared to frequentist showed that modeling GE using GGE biplot analysis  ... 
doi:10.3126/ijasbt.v3i2.11908 fatcat:7qwtacge4bc6pcjh7iebnkcixq

Regularizing Bayesian Predictive Regressions [article]

Guanhao Feng, Nicholas G. Polson
2017 arXiv   pre-print
We show that regularizing Bayesian predictive regressions provides a framework for prior sensitivity analysis.  ...  By exploiting a duality between regularization penalties and predictive prior distributions, we reinterpret two classic Bayesian analyses of macro-finance studies: equity premium predictability and forecasting  ...  Specifying one data-driven prior in the Bayesian predictive system is possible. We suggest one can view a regularization approach as a quick precursor to a more detailed full Bayesian analysis.  ... 
arXiv:1606.01701v4 fatcat:awf3f63yyfg2phqt4zqbnf6gam

Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty

David Bauder, Taras Bodnar, Nestor Parolya, Wolfgang Schmid
2020 Quantitative finance (Print)  
' and by the Swedish Research Council (VR) via the project 'Bayesian Analysis of Optimal Portfolios and Their Risk Measures'.  ...  Acknowledgments The authors would like to thank Professor Michael Dempster, Professor Jim Gatheral and two anonymous Reviewers for their helpful suggestions.  ...  The (objective) Bayesian approach leads to a larger value of the variance and to a smaller value of the slope parameter.  ... 
doi:10.1080/14697688.2020.1748214 fatcat:ka7k4jmbgbdgdbfumgwtidvnyi

Strategic Bayesian Asset Allocation [article]

Vadim Sokolov, Michael Polson
2019 arXiv   pre-print
Our approach uses Bayesian regularization to not only provide stock selection but also optimal sequential portfolio weights.  ...  We illustrate our methodology on stock selection from the SP100 stock index and from the top fifty holdings of two hedge funds Renaissance Technologies and Viking Global.  ...  The investor's objective is to minimize the variance (risk) of the portfolio while having a guaranteed return ρ.  ... 
arXiv:1905.08414v2 fatcat:eywy3myeezesfa5cwdww5tptjq

Comparison of Neural Network, Bayesian, and Multiple Stepwise Regression–Based Limited Sampling Models to Estimate Area Under the Curve

Chee M. Ng
2003 Pharmacotherapy  
p<0.05 for stepwise and neural network comparison p<0.05 for Bayesian approach and neural network omparison based on the Friedman one-way repeated measures analysis of variance on rank followed by Student-Newman-Keuls  ...  Eq. 3 Nn i=l The MPE and MSE were tested by Friedman one- way repeated measures analysis of variance on rank, followed by Student-Newman-Keuls test for multiple comparisons.  ... 
doi:10.1592/phco.23.8.1044.32872 pmid:12921250 fatcat:ql3eaezouve2vam6g45beb3jmm

Using classical psychometric testing and rasch analysis to refine a new weight specific quality of life measure for adolescents

Y Oluboyede
2013 Value in Health  
A Bayesian approach has the advantage of being able to provide probability statements for equivalence, to make direct inferential statement that the treatment effect between the two comparisons is between  ...  We compared the results of the Bayesian model with a WIP (coefficients are assigned a N(0,1.38) prior) to results of deleting the problematic variable, exact logistic regression and two different algorithms  ...  A Bayesian approach has the advantage of being able to provide probability statements for equivalence, to make direct inferential statement that the treatment effect between the two comparisons is between  ... 
doi:10.1016/j.jval.2013.03.278 fatcat:m4am7zn2kjat5fejo3cehp3liq

A Comparison of Empirical Bayes and Reference Prior Methods for Spatio-Temporal Data Analysis

Firoozeh Rivaz
2011 Procedia Environmental Sciences  
In Bayesian analysis of spatio-temporal data, the problem of selecting prior distribution for model parameters is of great demand.  ...  This paper considers two most popular approaches, empirical Bayes and reference prior, for Bayesian inference. We then use simulation to compare the frequentist properties of these two methods.  ...  By this way, one does not need to verify posterior existence. The other approach is objective Bayesian analysis that uses default priors.  ... 
doi:10.1016/j.proenv.2011.07.046 fatcat:pympz5itybcp5gd4qo4y7xgql4

Bayesian inference of genetic parameters and selection response for litter size components in pigs

A Blasco, D Sorensen, J P Bidanel
1998 Genetics  
In the second line, they were selected for prenatal survival of the first two parities, corrected for ovulation rate. The control constituted the third line.  ...  The mean of the marginal posterior distribution of response to four generations of selection ranged from 0.38 to 0.40 ova per generation, and from 1.1 to 1.3% of the mean survival rate for average survival  ...  The objective of this paper is to report an analysis MATERIALS precise estimate of the sampling variance of the estima-Estrus detection on a daily basis was initiated at 150 days of tor of selection  ... 
pmid:9584104 pmcid:PMC1460131 fatcat:sw4i5brhdzde3lgup6onaflz3y

Model Fitting and Model Evidence for Multiscale Image Texture Analysis

Mihai Datcu
2004 AIP Conference Proceedings  
This paper, begins with an overview of the two levels of Bayesian inference: model fitting and model selection, and shows how they can be used for the image texture analysis.  ...  This paper, in the first part, begins with an overview of the application of the two levels of Bayesian inference, model fitting and model selection, for the texture parameters estimation and the selection  ...  BAYESIAN IMAGE TEXTURE ANALYSIS There are several approaches to analyze the image textures in a Bayesian frame. Some of them are based on fitting a parametric model to the image data.  ... 
doi:10.1063/1.1835195 fatcat:sfnmeqrr5zajxapfmioj4zwd7m

Bayesian Joint Modelling of Longitudinal and Survival Data of HIV/AIDS Patients: A Case Study at Bale Robe General Hospital, Ethiopia

Ahmed Hasan Dessiso
2017 American Journal of Theoretical and Applied Statistics  
The objective is to develop separate and joint statistical models in the Bayesian framework for longitudinal measurements and time to death event data of HIV/AIDS patients.  ...  The analysis of both the separate and the joint models reveal that the assumption of heterogeneous (patient-specific) CD4 variances brings improvement in the model fit.  ...  The second term Results The objective of this study was to model the longitudinal measurements of CD4 counts per B of blood and the associated time to death using the Bayesian joint modelling approach  ... 
doi:10.11648/j.ajtas.20170604.13 fatcat:7db5estswzcibixqipx7udtyf4

Data-Driven Bayesian Network Learning: Towards a Bi-Objective Approach to Address the Bias-Variance Decomposition

Vicente Josué Aguilera Rueda, Nicandro Cruz-Ramírez, Efrén Mezura-Montes
2020 Research on computing science  
The core idea is to reduce the implicit selection bias-variance decomposition while identifying a set of competitive models using both objectives.  ...  We present a novel bi-objective approach to address the data-driven learning problem of Bayesian networks.  ...  Introduction A way to build a Bayesian Network (BN) is adopting a data-driven inductive approach; in this case, the learning task is framed as a combinatorial optimization problem with two components:  ... 
dblp:journals/rcs/RuedaCM20 fatcat:le2d2fsjabbdxb7ot2uh4olava

Novel Bayesian Procrustes Variance-based Inferences in Geometric Morphometrics Novel R package: BPviGM1 [article]

Debashis Chatterjee
2021 arXiv   pre-print
discovery using morphological variation reflected in the posterior distribution of landmark-variance of objects studied under Geometric Morphometrics.  ...  Here we propose novel Bayesian methodologies for Procrustes shape analysis based on landmark data's isotropic variance assumption and propose a Bayesian statistical test for model validation of new species  ...  Acknowledgments Author thanks Geological Studies Unit of Indian Statistical Institute for providing motivations and encouragements to pursue research on novel bayesian methods for Geometric morphometrics  ... 
arXiv:2101.06494v2 fatcat:2345g66jvveg5ncbnbhf5uqywa

Using the weighted interval midpoint estimator (wime) to estimate a population mean from interval data

A.F. Magyar, B. Wang, W.E. Furnback
2013 Value in Health  
A Bayesian approach has the advantage of being able to provide probability statements for equivalence, to make direct inferential statement that the treatment effect between the two comparisons is between  ...  We compared the results of the Bayesian model with a WIP (coefficients are assigned a N(0,1.38) prior) to results of deleting the problematic variable, exact logistic regression and two different algorithms  ...  A Bayesian approach has the advantage of being able to provide probability statements for equivalence, to make direct inferential statement that the treatment effect between the two comparisons is between  ... 
doi:10.1016/j.jval.2013.03.276 fatcat:q673o77bcvb47ijllzcbgkgrpi

A caution about using sample means to estimate incremental costs for expenditures that follow a traditional gamma distribution with parameters for scale and shape

P Juneau
2013 Value in Health  
A Bayesian approach has the advantage of being able to provide probability statements for equivalence, to make direct inferential statement that the treatment effect between the two comparisons is between  ...  We compared the results of the Bayesian model with a WIP (coefficients are assigned a N(0,1.38) prior) to results of deleting the problematic variable, exact logistic regression and two different algorithms  ...  A Bayesian approach has the advantage of being able to provide probability statements for equivalence, to make direct inferential statement that the treatment effect between the two comparisons is between  ... 
doi:10.1016/j.jval.2013.03.277 fatcat:te7emupxx5apxcjdpf3sjybvri
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