IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v50y2006i2p346-357.html

Bayesian model choice based on Monte Carlo estimates of posterior model probabilities

Author

Listed:
  • Congdon, Peter

Abstract

No abstract is available for this item.

Suggested Citation

  • Congdon, Peter, 2006. "Bayesian model choice based on Monte Carlo estimates of posterior model probabilities," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 346-357, January.
    • Handle: RePEc:eee:csdana:v:50:y:2006:i:2:p:346-357
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(04)00246-4
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Kadane, Joseph B. & Lazar, Nicole A., 2004. "Methods and Criteria for Model Selection," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 279-290, January.
    2. Scott S. L., 2002. "Bayesian Methods for Hidden Markov Models: Recursive Computing in the 21st Century," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 337-351, March.
    3. Song, Xin-Yuan & Lee, Sik-Yum, 2002. "A Bayesian model selection method with applications," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 539-557, September.
    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. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2011. "Multi-regime nonlinear capital asset pricing models," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1421-1438, April.
    2. Gareth W. Peters & Pavel V. Shevchenko & Mario V. Wuthrich, 2009. "Model uncertainty in claims reserving within Tweedie's compound Poisson models," Papers 0904.1483, arXiv.org.
    3. Koulis Theodoro & Muthukumarana Saman & Briercliffe Creagh Dyson, 2014. "A Bayesian stochastic model for batting performance evaluation in one-day cricket," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(1), pages 1-13, January.
    4. Chkrebtii, Oksana A. & Cameron, Erin K. & Campbell, David A. & Bayne, Erin M., 2015. "Transdimensional approximate Bayesian computation for inference on invasive species models with latent variables of unknown dimension," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 97-110.
    5. Aßmann, Christian & Boysen-Hogrefe, Jens, 2011. "A Bayesian approach to model-based clustering for binary panel probit models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 261-279, January.
    6. Cathy Chen & Feng-Chi Liu & Mike So, 2013. "Threshold variable selection of asymmetric stochastic volatility models," Computational Statistics, Springer, vol. 28(6), pages 2415-2447, December.
    7. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.
    8. So, Mike K.P. & Chan, Raymond K.S., 2014. "Bayesian analysis of tail asymmetry based on a threshold extreme value model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 568-587.
    9. Rufo, M.J. & Martín, J. & Pérez, C.J., 2010. "New approaches to compute Bayes factor in finite mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3324-3335, December.
    10. Zongyuan Xia & Bo Tang & Long Qin & Huiguo Zhang & Xijian Hu, 2023. "Spatially Dependent Bayesian Modeling of Geostatistics Data and Its Application for Tuberculosis (TB) in China," Mathematics, MDPI, vol. 11(19), pages 1-15, October.
    11. Christian P. Robert, 2013. "Bayesian Computational Tools," Working Papers 2013-45, Center for Research in Economics and Statistics.
    12. F. Bartolucci & A. Farcomeni & F. Pennoni, 2014. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 433-465, September.
    13. Gelman Andrew & Robert Christian P. & Rousseau Judith, 2013. "Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin," Statistics & Risk Modeling, De Gruyter, vol. 30(2), pages 105-120, 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. Hedibert Freitas Lopes, 2014. "A Tutorial on the Computation of Bayes Factors," Business and Economics Working Papers 200, Unidade de Negocios e Economia, Insper.
    2. Jennifer Oser & Marc Hooghe & Zsuzsa Bakk & Roberto Mari, 2023. "Changing citizenship norms among adolescents, 1999-2009-2016: A two-step latent class approach with measurement equivalence testing," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4915-4933, October.
    3. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    4. Oscar Andrés Espinosa Acuna & Paola Andrea Vaca Gonz�lez, 2017. "Ajuste de modelos garch clásico y bayesiano con innovaciones t—student para el índice COLCAP," Revista de Economía del Caribe, Universidad del Norte, vol. 0(0), pages 1-32.
    5. Jamie McCann & Gerald M Schneeweiss & Tod F Stuessy & Jose L Villaseñor & Hanna Weiss-Schneeweiss, 2016. "The Impact of Reconstruction Methods, Phylogenetic Uncertainty and Branch Lengths on Inference of Chromosome Number Evolution in American Daisies (Melampodium, Asteraceae)," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-23, September.
    6. Hammer, Hugo & Tjelmeland, Håkon, 2011. "Approximate forward-backward algorithm for a switching linear Gaussian model," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 154-167, January.
    7. Kukkonen, M.O. & Khamis, M. & Muhammad, M.J. & Käyhkö, N. & Luoto, M., 2022. "Modeling direct above-ground carbon loss due to urban expansion in Zanzibar City Region, Tanzania," Land Use Policy, Elsevier, vol. 112(C).
    8. Kukkonen, Markus O. & Muhammad, Muhammad J. & Käyhkö, Niina & Luoto, Miska, 2018. "Urban expansion in Zanzibar City, Tanzania: Analyzing quantity, spatial patterns and effects of alternative planning approaches," Land Use Policy, Elsevier, vol. 71(C), pages 554-565.
    9. Kozumi, Hideo, 2004. "Posterior analysis of latent competing risk models by parallel tempering," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 441-458, June.
    10. Armin Falk & Anke Becker & Thomas Dohmen & David Huffman & Uwe Sunde, 2023. "The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences," Management Science, INFORMS, vol. 69(4), pages 1935-1950, April.
    11. J. Andrew Royle, 2009. "Analysis of Capture–Recapture Models with Individual Covariates Using Data Augmentation," Biometrics, The International Biometric Society, vol. 65(1), pages 267-274, March.
    12. Scott, Steven L., 2004. "A Bayesian paradigm for designing intrusion detection systems," Computational Statistics & Data Analysis, Elsevier, vol. 45(1), pages 69-83, February.
    13. Ward, Eric J., 2008. "A review and comparison of four commonly used Bayesian and maximum likelihood model selection tools," Ecological Modelling, Elsevier, vol. 211(1), pages 1-10.
    14. Francesco Dotto & Alessio Farcomeni & Maria Grazia Pittau & Roberto Zelli, 2019. "A dynamic inhomogeneous latent state model for measuring material deprivation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 495-516, February.
    15. Kassie, Girma T. & Abdulai, Awudu & Greene, William H. & Shiferaw, Bekele & Abate, Tsedeke & Tarekegne, Amsal & Sutcliffe, Chloe, 2017. "Modeling Preference and Willingness to Pay for Drought Tolerance (DT) in Maize in Rural Zimbabwe," World Development, Elsevier, vol. 94(C), pages 465-477.
    16. Bezanesh Melese Masresha & Kasim Mohammed Yesuf & Yikeber Abebaw Moyehodie & Hailegebrael Birhan Biresaw & Solomon Sisay Mulugeta & Gedam Derbew Addisia, 2023. "Determinant factors of leprosy-related disability; comparison of acceleration failure time and parametric shared frailty models," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-26, April.
    17. Narander Kumar Nigam & C. P. Gupta, 2021. "Correlation-based Diversification and Firm Performance: An Empirical Investigation of India," Global Business Review, International Management Institute, vol. 22(2), pages 442-458, April.
    18. Elena DRUICA & Roxana ADAM, 2015. "Logistic Regression Models: Reassessing The Determinants Of Product Innovation Using Romanian Survey Data," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 4(2), pages 1-18, DECEMBER.
    19. Guedon, Yann, 2007. "Exploring the state sequence space for hidden Markov and semi-Markov chains," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2379-2409, February.
    20. R. B. Millar & S. McKechnie, 2014. "A one-step-ahead pseudo-DIC for comparison of Bayesian state-space models," Biometrics, The International Biometric Society, vol. 70(4), pages 972-980, December.

    More about this item

    Statistics

    Access and download statistics

    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:eee:csdana:v:50:y:2006:i:2:p:346-357. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.