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Bayesian Latent Factor Regression for Functional and Longitudinal Data

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  • Silvia Montagna
  • Surya T. Tokdar
  • Brian Neelon
  • David B. Dunson

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  • Silvia Montagna & Surya T. Tokdar & Brian Neelon & David B. Dunson, 2012. "Bayesian Latent Factor Regression for Functional and Longitudinal Data," Biometrics, The International Biometric Society, vol. 68(4), pages 1064-1073, December.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:4:p:1064-1073
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2012.01788.x
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    References listed on IDEAS

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    2. Reiss Philip T. & Huang Lei & Mennes Maarten, 2010. "Fast Function-on-Scalar Regression with Penalized Basis Expansions," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-30, August.
    3. David B. Dunson, 2009. "Nonparametric Bayes local partition models for random effects," Biometrika, Biometrika Trust, vol. 96(2), pages 249-262.
    4. Sam Behseta & Robert E. Kass & Garrick L. Wallstrom, 2005. "Hierarchical models for assessing variability among functions," Biometrika, Biometrika Trust, vol. 92(2), pages 419-434, June.
    5. Bigelow, Jamie L. & Dunson, David B., 2009. "Bayesian Semiparametric Joint Models for Functional Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 26-36.
    6. Rolando De la Cruz‐Mesía & Fernando A. Quintana & Peter Müller, 2007. "Semiparametric Bayesian classification with longitudinal markers," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(2), pages 119-137, March.
    7. Yao, Fang & Muller, Hans-Georg & Wang, Jane-Ling, 2005. "Functional Data Analysis for Sparse Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 577-590, June.
    8. A. Bhattacharya & D. B. Dunson, 2011. "Sparse Bayesian infinite factor models," Biometrika, Biometrika Trust, vol. 98(2), pages 291-306.
    9. Shubhankar Ray & Bani Mallick, 2006. "Functional clustering by Bayesian wavelet methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 305-332, April.
    10. Sonia Petrone & Michele Guindani & Alan E. Gelfand, 2009. "Hybrid Dirichlet mixture models for functional data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(4), pages 755-782, September.
    11. Gerhard Arminger & Bengt Muthén, 1998. "A Bayesian approach to nonlinear latent variable models using the Gibbs sampler and the metropolis-hastings algorithm," Psychometrika, Springer;The Psychometric Society, vol. 63(3), pages 271-300, September.
    12. Abel Rodríguez & David B. Dunson & Alan E. Gelfand, 2009. "Bayesian nonparametric functional data analysis through density estimation," Biometrika, Biometrika Trust, vol. 96(1), pages 149-162.
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    Cited by:

    1. Matthew W. Wheeler, 2019. "Bayesian additive adaptive basis tensor product models for modeling high dimensional surfaces: an application to high‐throughput toxicity testing," Biometrics, The International Biometric Society, vol. 75(1), pages 193-201, March.
    2. Patric Dolmeta & Raffaele Argiento & Silvia Montagna, 2023. "Bayesian GARCH modeling of functional sports data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 401-423, June.
    3. Pantelis Samartsidis & Shaun R. Seaman & Silvia Montagna & André Charlett & Matthew Hickman & Daniela De Angelis, 2020. "A Bayesian multivariate factor analysis model for evaluating an intervention by using observational time series data on multiple outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1437-1459, October.
    4. Mark J. Meyer & Brent A. Coull & Francesco Versace & Paul Cinciripini & Jeffrey S. Morris, 2015. "Bayesian function‐on‐function regression for multilevel functional data," Biometrics, The International Biometric Society, vol. 71(3), pages 563-574, September.
    5. Cui Guo & Jian Kang & Timothy D. Johnson, 2022. "A spatial Bayesian latent factor model for image‐on‐image regression," Biometrics, The International Biometric Society, vol. 78(1), pages 72-84, March.
    6. Silvia Montagna & Tor Wager & Lisa Feldman Barrett & Timothy D. Johnson & Thomas E. Nichols, 2018. "Spatial Bayesian latent factor regression modeling of coordinate†based meta†analysis data," Biometrics, The International Biometric Society, vol. 74(1), pages 342-353, March.
    7. L Schiavon & A Canale & D B Dunson, 2022. "Generalized infinite factorization models [A latent factor linear mixed model for high-dimensional longitudinal data analysis]," Biometrika, Biometrika Trust, vol. 109(3), pages 817-835.
    8. Jaeeun Yu & Jinsu Park & Taeryon Choi & Masahiro Hashizume & Yoonhee Kim & Yasushi Honda & Yeonseung Chung, 2021. "Nonparametric Bayesian Functional Meta-Regression: Applications in Environmental Epidemiology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(1), pages 45-70, March.
    9. Durante, Daniele, 2017. "A note on the multiplicative gamma process," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 198-204.
    10. Brown, Sarah & Ghosh, Pulak & Su, Li & Taylor, Karl, 2015. "Modelling household finances: A Bayesian approach to a multivariate two-part model," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 190-207.
    11. Luca Aiello & Matteo Fontana & Alessandra Guglielmi, 2023. "Bayesian functional emulation of CO2 emissions on future climate change scenarios," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.
    12. Daniel R. Kowal & Antonio Canale, 2021. "Semiparametric Functional Factor Models with Bayesian Rank Selection," Papers 2108.02151, arXiv.org, revised May 2022.
    13. Daewon Yang & Taeryon Choi & Eric Lavigne & Yeonseung Chung, 2022. "Non‐parametric Bayesian covariate‐dependent multivariate functional clustering: An application to time‐series data for multiple air pollutants," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1521-1542, November.

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