Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. II: Multivariate spike and slab priors for marker effects and derivation of approximate Bayes and fractional Bayes factors for the complete family of models

Journal of Theoretical Biology ◽

10.1016/j.jtbi.2016.12.022 ◽

2017 ◽

Vol 417 ◽

pp. 131-141 ◽

Cited By ~ 1

Author(s):

Carlos Alberto Martínez ◽

Kshitij Khare ◽

Arunava Banerjee ◽

Mauricio A. Elzo

Keyword(s):

Hierarchical Bayes ◽

Bayes Factors ◽

Complete Family ◽

Genome Wide ◽

Bayes Approach

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Empirical Hierarchical Bayes Approach to Gene-Environment Interactions: Development and Application to Genome-Wide Association Studies of Lung Cancer in TRICL

Genetic Epidemiology ◽

10.1002/gepi.21741 ◽

2013 ◽

Vol 37 (6) ◽

pp. 551-559 ◽

Cited By ~ 5

Author(s):

Melanie Sohns ◽

Elena Viktorova ◽

Christopher I. Amos ◽

Paul Brennan ◽

Gord Fehringer ◽

...

Keyword(s):

Lung Cancer ◽

Association Studies ◽

Hierarchical Bayes ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Gene Environment ◽

Genome Wide ◽

Bayes Approach

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Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes

Journal of Theoretical Biology ◽

10.1016/j.jtbi.2016.12.020 ◽

2017 ◽

Vol 417 ◽

pp. 8-19 ◽

Cited By ~ 1

Author(s):

Carlos Alberto Martínez ◽

Kshitij Khare ◽

Arunava Banerjee ◽

Mauricio A. Elzo

Keyword(s):

Joint Probability ◽

Mass Function ◽

Hierarchical Bayes ◽

Probability Mass Function ◽

Genome Wide ◽

Multivariate Gaussian ◽

Probability Mass ◽

Bayes Approach

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Hierarchical Bayes approach to adapting delta- and delta-delta cepstra

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100) ◽

10.1109/icassp.2000.859124 ◽

2002 ◽

Cited By ~ 2

Author(s):

A.C. Surendran

Keyword(s):

Hierarchical Bayes ◽

Bayes Approach

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A hierarchical Bayes approach to nonlinear time series prediction with neural nets

Proceedings of International Conference on Neural Networks (ICNN'97) ◽

10.1109/icnn.1997.614213 ◽

2002 ◽

Cited By ~ 4

Author(s):

T. Matsumoto ◽

H. Hamagishi ◽

Y. Chonan

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Nonlinear Time Series ◽

Hierarchical Bayes ◽

Neural Nets ◽

Bayes Approach

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Hybrid Bayes factors for genome-wide association studies when a robust test is used

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2011.03.021 ◽

2011 ◽

Vol 55 (9) ◽

pp. 2698-2711 ◽

Cited By ~ 2

Author(s):

Gang Zheng ◽

Ao Yuan ◽

Neal Jeffries

Keyword(s):

Association Studies ◽

Bayes Factors ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Robust Test ◽

Genome Wide

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Bayes factors for genome-wide association studies: comparison withP-values

Genetic Epidemiology ◽

10.1002/gepi.20359 ◽

2009 ◽

Vol 33 (1) ◽

pp. 79-86 ◽

Cited By ~ 227

Author(s):

Jon Wakefield

Keyword(s):

Association Studies ◽

Bayes Factors ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Commentary: Genome-wide significance thresholds via Bayes factors

International Journal of Epidemiology ◽

10.1093/ije/dyr241 ◽

2012 ◽

Vol 41 (1) ◽

pp. 286-291 ◽

Cited By ~ 7

Author(s):

Jon Wakefield

Keyword(s):

Bayes Factors ◽

Genome Wide ◽

Genome Wide Significance

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From data to nonlinear dynamics: a hierarchical Bayes approach with neural nets

Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378) ◽

10.1109/nnsp.1998.710663 ◽

2002 ◽

Cited By ~ 7

Author(s):

T. Matsumoto ◽

Y. Nakajima ◽

H. Hamagishi ◽

J. Sugi ◽

M. Saito

Keyword(s):

Nonlinear Dynamics ◽

Hierarchical Bayes ◽

Neural Nets ◽

Bayes Approach

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Hierarchical Bayes Approach for Analysis of Item-Level Missing Data

International Journal of Clinical Biostatistics and Biometrics ◽

10.23937/2469-5831/1510009 ◽

2016 ◽

Vol 2 (1) ◽

Author(s):

Junshan Qiu

Keyword(s):

Missing Data ◽

Hierarchical Bayes ◽

Item Level ◽

Bayes Approach

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Small area estimation of general parameters with application to poverty indicators: A hierarchical Bayes approach

The Annals of Applied Statistics ◽

10.1214/13-aoas702 ◽

2014 ◽

Vol 8 (2) ◽

pp. 852-885 ◽

Cited By ~ 37

Author(s):

Isabel Molina ◽

Balgobin Nandram ◽

J. N. K. Rao

Keyword(s):

Small Area ◽

Small Area Estimation ◽

Hierarchical Bayes ◽

Area Estimation ◽

Poverty Indicators ◽

Bayes Approach

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