IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v110y2016icp278-288.html
   My bibliography  Save this article

On asymptotics related to classical inference in stochastic differential equations with random effects

Author

Listed:
  • Maitra, Trisha
  • Bhattacharya, Sourabh

Abstract

Delattre et al. (2013) considered n independent stochastic differential equations (SDE’s), where in each case the drift term is associated with a random effect, the distribution of which depends upon unknown parameters. Assuming the independent and identical (iid) situation the authors provide independent proofs of weak consistency and asymptotic normality of the maximum likelihood estimators (MLE’s) of the hyper-parameters of their random effects parameters.

Suggested Citation

  • Maitra, Trisha & Bhattacharya, Sourabh, 2016. "On asymptotics related to classical inference in stochastic differential equations with random effects," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 278-288.
    • Handle: RePEc:eee:stapro:v:110:y:2016:i:c:p:278-288
    DOI: 10.1016/j.spl.2015.10.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715215003442
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2015.10.001?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. Maud Delattre & Valentine Genon-Catalot & Adeline Samson, 2013. "Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(2), pages 322-343, June.
    2. Maitra, Trisha & Bhattacharya, Sourabh, 2015. "On Bayesian asymptotics in stochastic differential equations with random effects," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 148-159.
    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. Dai, Min & Duan, Jinqiao & Liao, Junjun & Wang, Xiangjun, 2021. "Maximum likelihood estimation of stochastic differential equations with random effects driven by fractional Brownian motion," Applied Mathematics and Computation, Elsevier, vol. 397(C).

    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. Delattre, Maud & Genon-Catalot, Valentine & Larédo, Catherine, 2018. "Parametric inference for discrete observations of diffusion processes with mixed effects," Stochastic Processes and their Applications, Elsevier, vol. 128(6), pages 1929-1957.
    2. Maitra, Trisha & Bhattacharya, Sourabh, 2015. "On Bayesian asymptotics in stochastic differential equations with random effects," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 148-159.
    3. Nelson T. Jamba & Gonçalo Jacinto & Patrícia A. Filipe & Carlos A. Braumann, 2022. "Likelihood Function through the Delta Approximation in Mixed SDE Models," Mathematics, MDPI, vol. 10(3), pages 1-20, January.
    4. Dai, Min & Duan, Jinqiao & Liao, Junjun & Wang, Xiangjun, 2021. "Maximum likelihood estimation of stochastic differential equations with random effects driven by fractional Brownian motion," Applied Mathematics and Computation, Elsevier, vol. 397(C).

    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:stapro:v:110:y:2016:i:c:p:278-288. 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/wps/find/journaldescription.cws_home/622892/description#description .

    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.