IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v66y2010i3p742-752.html
   My bibliography  Save this article

Semi-Markov Models with Phase-Type Sojourn Distributions

Author

Listed:
  • Andrew C. Titman
  • Linda D. Sharples

Abstract

No abstract is available for this item.

Suggested Citation

  • Andrew C. Titman & Linda D. Sharples, 2010. "Semi-Markov Models with Phase-Type Sojourn Distributions," Biometrics, The International Biometric Society, vol. 66(3), pages 742-752, September.
  • Handle: RePEc:bla:biomet:v:66:y:2010:i:3:p:742-752
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01339.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Glen A. Satten & Maya R. Sternberg, 1999. "Fitting Semi-Markov Models to Interval-Censored Data with Unknown Initiation Times," Biometrics, The International Biometric Society, vol. 55(2), pages 507-513, June.
    2. Catherine M. Crespi & William G. Cumberland & Sally Blower, 2005. "A Queueing Model for Chronic Recurrent Conditions under Panel Observation," Biometrics, The International Biometric Society, vol. 61(1), pages 193-198, March.
    3. Hanfeng Chen & Jiahua Chen & John D. Kalbfleisch, 2001. "A modified likelihood ratio test for homogeneity in finite mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 19-29.
    4. Yuguo Chen & Junyi Xie & Jun S. Liu, 2005. "Stopping‐time resampling for sequential Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 199-217, April.
    5. Pierre Joly & Daniel Commenges, 1999. "A Penalized Likelihood Approach for a Progressive Three-State Model with Censored and Truncated Data: Application to AIDS," Biometrics, The International Biometric Society, vol. 55(3), pages 887-890, 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. Vernon T. Farewell & Li Su & Christopher Jackson, 2019. "Partially hidden multi-state modelling of a prolonged disease state defined by a composite outcome," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 696-711, October.
    2. Chu-Chih Chen & , Chuan-Pin Lee & Yuan-Horng Yan & Tsun-Jen Cheng & Pranab K. Sen, 2021. "A partial likelihood-based two-dimensional multistate markov model with application to myocardial infarction and stroke recurrence," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 282-303, November.
    3. Jane M. Lange & Rebecca A. Hubbard & Lurdes Y. T. Inoue & Vladimir N. Minin, 2015. "A joint model for multistate disease processes and random informative observation times, with applications to electronic medical records data," Biometrics, The International Biometric Society, vol. 71(1), pages 90-101, March.
    4. Boumezoued, Alexandre & Karoui, Nicole El & Loisel, Stéphane, 2017. "Measuring mortality heterogeneity with multi-state models and interval-censored data," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 67-82.

    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. Marc Chadeau‐Hyam & Paul S. Clarke & Chantal Guihenneuc‐Jouyaux & Simon N. Cousens & Robert G. Will & Azra C. Ghani, 2010. "An application of hidden Markov models to the French variant Creutzfeldt–Jakob disease epidemic," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 839-853, November.
    2. E. Mathieu & Y. Foucher & P. Dellamonica & J. P. Daures, 2007. "Parametric and Non Homogeneous Semi-Markov Process for HIV Control," Methodology and Computing in Applied Probability, Springer, vol. 9(3), pages 389-397, September.
    3. Daeyoung Kim & Bruce Lindsay, 2015. "Empirical identifiability in finite mixture models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 745-772, August.
    4. Ye, Mao & Lu, Zhao-Hua & Li, Yimei & Song, Xinyuan, 2019. "Finite mixture of varying coefficient model: Estimation and component selection," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 452-474.
    5. Proust-Lima, Cécile & Joly, Pierre & Dartigues, Jean-François & Jacqmin-Gadda, Hélène, 2009. "Joint modelling of multivariate longitudinal outcomes and a time-to-event: A nonlinear latent class approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1142-1154, February.
    6. Zhu, Hongtu & Zhang, Heping, 2006. "Asymptotics for estimation and testing procedures under loss of identifiability," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 19-45, January.
    7. Meng Li & Sijia Xiang & Weixin Yao, 2016. "Robust estimation of the number of components for mixtures of linear regression models," Computational Statistics, Springer, vol. 31(4), pages 1539-1555, December.
    8. Andrew Sweeting, 2009. "The strategic timing incentives of commercial radio stations: An empirical analysis using multiple equilibria," RAND Journal of Economics, RAND Corporation, vol. 40(4), pages 710-742, December.
    9. Alexander D. Stead & Phill Wheat & William H. Greene, 2023. "On hypothesis testing in latent class and finite mixture stochastic frontier models, with application to a contaminated normal-half normal model," Journal of Productivity Analysis, Springer, vol. 60(1), pages 37-48, August.
    10. Moming Li & Guoqing Diao & Jing Qin, 2020. "On symmetric semiparametric two‐sample problem," Biometrics, The International Biometric Society, vol. 76(4), pages 1216-1228, December.
    11. Dante Amengual & Xinyue Bei & Marine Carrasco & Enrique Sentana, 2022. "Score-type tests for normal mixtures," Working Papers wp2022_2213, CEMFI.
    12. Hoshino Tadao & Yanagi Takahide, 2022. "Estimating marginal treatment effects under unobserved group heterogeneity," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 197-216, January.
    13. Catherine M. Crespi & Kenneth Lange, 2006. "Estimation for the Simple Linear Boolean Model," Methodology and Computing in Applied Probability, Springer, vol. 8(4), pages 559-571, December.
    14. Jung Yeon Lee & Myeong-Kyu Kim & Wonkuk Kim, 2020. "Robust Linear Trend Test for Low-Coverage Next-Generation Sequence Data Controlling for Covariates," Mathematics, MDPI, vol. 8(2), pages 1-14, February.
    15. Derek S. Young & Xi Chen & Dilrukshi C. Hewage & Ricardo Nilo-Poyanco, 2019. "Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 1053-1082, December.
    16. B. A. Griffin & S. W. Lagakos, 2008. "Design and Analysis of Arm-in-Cage Experiments: Inference for Three-State Progressive Disease Models with Common Periodic Observation Times," Biometrics, The International Biometric Society, vol. 64(2), pages 337-344, June.
    17. Nicoleta Serban, 2007. "MICE: Multiple-Peak Identification, Characterization, and Estimation," Biometrics, The International Biometric Society, vol. 63(2), pages 531-539, June.
    18. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
    19. Andrea Arfè & Stefano Peluso & Pietro Muliere, 2021. "The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes," Statistical Inference for Stochastic Processes, Springer, vol. 24(1), pages 1-15, April.
    20. Ian Dinwoodie & Kruti Pandya, 2015. "Exact tests for singular network data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 687-706, August.

    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:biomet:v:66:y:2010:i:3:p:742-752. 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: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.