IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v66y2017i2p387-412.html
   My bibliography  Save this article

A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions

Author

Listed:
  • Vinícius Diniz Mayrink
  • Flávio Bambirra Gonçalves

Abstract

No abstract is available for this item.

Suggested Citation

  • Vinícius Diniz Mayrink & Flávio Bambirra Gonçalves, 2017. "A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 387-412, February.
    • Handle: RePEc:bla:jorssc:v:66:y:2017:i:2:p:387-412
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssc.12178
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    for a different version of it.

    References listed on IDEAS

    as
    1. Kim‐Anh Do & Peter Müller & Feng Tang, 2005. "A Bayesian mixture model for differential gene expression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 627-644, June.
    2. Alexandros Beskos & Omiros Papaspiliopoulos & Gareth O. Roberts & Paul Fearnhead, 2006. "Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 333-382, June.
    3. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    4. Giovanni Parmigiani & Elizabeth S. Garrett & Ramaswamy Anbazhagan & Edward Gabrielson, 2002. "A statistical framework for expression‐based molecular classification in cancer," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 717-736, October.
    5. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    6. Lewin Alex & Bochkina Natalia & Richardson Sylvia, 2007. "Fully Bayesian Mixture Model for Differential Gene Expression: Simulations and Model Checks," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 6(1), pages 1-28, December.
    7. James H. Albert, 1992. "Bayesian Estimation of Normal Ogive Item Response Curves Using Gibbs Sampling," Journal of Educational and Behavioral Statistics, , vol. 17(3), pages 251-269, 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. Vinícius Diniz Mayrink & Flávio B. Gonçalves, 2020. "Identifying atypically expressed chromosome regions using RNA-Seq data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 619-649, September.

    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. Vinícius Diniz Mayrink & Flávio B. Gonçalves, 2020. "Identifying atypically expressed chromosome regions using RNA-Seq data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 619-649, September.
    2. E. M. Conlon & B. L. Postier & B. A. Methe & K. P. Nevin & D. R. Lovley, 2009. "Hierarchical Bayesian meta-analysis models for cross-platform microarray studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1067-1085.
    3. Rossell David & Guerra Rudy & Scott Clayton, 2008. "Semi-Parametric Differential Expression Analysis via Partial Mixture Estimation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-29, April.
    4. Bae, Jinho & Nelson, Charles R., 2007. "Earnings growth and the bull market of the 1990s: Is there a case for rational exuberance?," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 690-707, December.
    5. Guohuan Su & Adam Mertel & Sébastien Brosse & Justin M. Calabrese, 2023. "Species invasiveness and community invasibility of North American freshwater fish fauna revealed via trait-based analysis," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Jinho Bae & Chang-Jin Kim & Dong Kim, 2012. "The evolution of the monetary policy regimes in the U.S," Empirical Economics, Springer, vol. 43(2), pages 617-649, October.
    7. Brandt, Patrick T. & George, Justin & Sandler, Todd, 2016. "Why concessions should not be made to terrorist kidnappers," European Journal of Political Economy, Elsevier, vol. 44(C), pages 41-52.
    8. Jaehee Kim & Sooyoung Cheon, 2010. "A Bayesian regime‐switching time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 365-378, September.
    9. Steven Andrew Culpepper & James Joseph Balamuta, 2017. "A Hierarchical Model for Accuracy and Choice on Standardized Tests," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 820-845, September.
    10. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2024. "Blended identification in structural VARs," Journal of Monetary Economics, Elsevier, vol. 146(C).
    11. Kim, Young Min & Lee, Seojin, 2023. "Spillover shifts in the FX market: Implication for the behavior of a safe haven currency," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    12. Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
    13. Stefano Fasani & Giuseppe Pagano Giorgianni & Valeria Patella & Lorenza Rossi, 2024. "Belief Distortions and Disagreement about Inflation," Working Paper series 24-08, Rimini Centre for Economic Analysis, revised May 2025.
    14. Meilan An & Jeffrey Vitale & Kwideok Han & John N. Ng’ombe & Inbae Ji, 2021. "Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
    15. Olga Demidova, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    16. Gomez, Manuel & Melvin, Michael & Nardari, Federico, 2007. "Explaining the early years of the euro exchange rate: An episode of learning about a new central bank," European Economic Review, Elsevier, vol. 51(3), pages 505-520, April.
    17. Varughese, Melvin M., 2013. "Parameter estimation for multivariate diffusion systems," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 417-428.
    18. Ruggieri, Eric & Antonellis, Marcus, 2016. "An exact approach to Bayesian sequential change point detection," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 71-86.
    19. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    20. Anoek Castelein & Dennis Fok & Richard Paap, 2020. "A multinomial and rank-ordered logit model with inter- and intra-individual heteroscedasticity," Tinbergen Institute Discussion Papers 20-069/III, Tinbergen Institute.

    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:bla:jorssc:v:66:y:2017:i:2:p:387-412. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.