IDEAS home Printed from https://ideas.repec.org/a/spr/alstar/v93y2009i3p307-333.html
   My bibliography  Save this article

A Bayesian latent variable approach to functional principal components analysis with binary and count data

Author

Listed:
  • Angelika Linde

Abstract

No abstract is available for this item.

Suggested Citation

  • Angelika Linde, 2009. "A Bayesian latent variable approach to functional principal components analysis with binary and count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 93(3), pages 307-333, September.
    • Handle: RePEc:spr:alstar:v:93:y:2009:i:3:p:307-333
    DOI: 10.1007/s10182-009-0113-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10182-009-0113-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10182-009-0113-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Michel Wedel & Wagner Kamakura, 2001. "Factor analysis with (mixed) observed and latent variables in the exponential family," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 515-530, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Ruizhi & Wang, Jian & Mei, Yajun, 2017. "Search for evergreens in science: A functional data analysis," Journal of Informetrics, Elsevier, vol. 11(3), pages 629-644.
    2. Bharath, Karthik, 2013. "A note on density estimation for binary sequences," Statistics & Probability Letters, Elsevier, vol. 83(12), pages 2735-2742.
    3. Daniel Backenroth & Russell T. Shinohara & Jennifer A. Schrack & Jeff Goldsmith, 2020. "Nonnegative decomposition of functional count data," Biometrics, The International Biometric Society, vol. 76(4), pages 1273-1284, December.
    4. Jeff Goldsmith & Vadim Zipunnikov & Jennifer Schrack, 2015. "Generalized multilevel function-on-scalar regression and principal component analysis," Biometrics, The International Biometric Society, vol. 71(2), pages 344-353, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Karsten Hansen & Vishal Singh & Pradeep Chintagunta, 2006. "Understanding Store-Brand Purchase Behavior Across Categories," Marketing Science, INFORMS, vol. 25(1), pages 75-90, 01-02.
    2. Ligon, Ethan, 2017. "Estimating household welfare from disaggregate expenditures," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5gc4h1fm, Department of Agricultural & Resource Economics, UC Berkeley.
    3. A. Kamakura, Wagner & Afonso Mazzon, Jose & De Bruyn, Arnaud, 2006. "Modeling voter choice to predict the final outcome of two-stage elections," International Journal of Forecasting, Elsevier, vol. 22(4), pages 689-706.
    4. Bruno Scarpa & David B. Dunson, 2014. "Enriched Stick-Breaking Processes for Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 647-660, June.
    5. Kim, Hea-Jung & Choi, Taeryon & Jo, Seongil, 2016. "Bayesian factor analysis with uncertain functional constraints about factor loadings," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 110-128.
    6. Nussbaum, Frank & Giesen, Joachim, 2020. "Pairwise sparse + low-rank models for variables of mixed type," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    7. Wagner Kamakura & Suman Basuroy & Peter Boatwright, 2006. "Is silence golden? An inquiry into the meaning of silence in professional product evaluations," Quantitative Marketing and Economics (QME), Springer, vol. 4(2), pages 119-141, June.
    8. Athanasios Kottas & Sam Behseta, 2010. "Bayesian Nonparametric Modeling for Comparison of Single-Neuron Firing Intensities," Biometrics, The International Biometric Society, vol. 66(1), pages 277-286, March.
    9. Becher, Michael & Stegmueller, Daniel, 2019. "Cognitive Ability, Union Membership, and Voter Turnout," IAST Working Papers 19-97, Institute for Advanced Study in Toulouse (IAST).
    10. Botts, Carsten H. & Daniels, Michael J., 2008. "A flexible approach to Bayesian multiple curve fitting," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5100-5120, August.
    11. Qian, Zhiguang & Shapiro, Alexander, 2006. "Simulation-based approach to estimation of latent variable models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1243-1259, November.
    12. Che Wan Jasimah Bt Wan Mohamed Radzi & Hashem Salarzadeh Jenatabadi & Maisarah Binti Hasbullah, 2015. "Firm Sustainability Performance Index Modeling," Sustainability, MDPI, vol. 7(12), pages 1-17, December.
    13. Sonja Radas & Drazen Prelec, 2019. "Whose data can we trust: How meta-predictions can be used to uncover credible respondents in survey data," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-16, December.
    14. van der Linde, Angelika, 2008. "Variational Bayesian functional PCA," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 517-533, December.
    15. Dimick, Matthew & Stegmueller, Daniel, 2015. "The Political Economy of Risk and Ideology," CAGE Online Working Paper Series 237, Competitive Advantage in the Global Economy (CAGE).
    16. Hui, Francis K.C. & Müller, Samuel & Welsh, A.H., 2020. "The LASSO on latent indices for regression modeling with ordinal categorical predictors," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).
    17. Prasad Naik & Michel Wedel & Lynd Bacon & Anand Bodapati & Eric Bradlow & Wagner Kamakura & Jeffrey Kreulen & Peter Lenk & David Madigan & Alan Montgomery, 2008. "Challenges and opportunities in high-dimensional choice data analyses," Marketing Letters, Springer, vol. 19(3), pages 201-213, December.
    18. Moon, Sangkil & Kamakura, Wagner A., 2017. "A picture is worth a thousand words: Translating product reviews into a product positioning map," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 265-285.
    19. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.
    20. Kamakura, Wagner A. & Mazzon, Jose A., 2013. "Socioeconomic status and consumption in an emerging economy," International Journal of Research in Marketing, Elsevier, vol. 30(1), pages 4-18.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:alstar:v:93:y:2009:i:3:p:307-333. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.