IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v45y2004i3p389-421.html

A new algorithm for estimating the parameters and their asymptotic covariance in correlation and association models

Author

Listed:
  • Ait-Sidi-Allal, M. L.
  • Baccini, A.
  • Mondot, A. M.

Abstract

No abstract is available for this item.

Suggested Citation

  • Ait-Sidi-Allal, M. L. & Baccini, A. & Mondot, A. M., 2004. "A new algorithm for estimating the parameters and their asymptotic covariance in correlation and association models," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 389-421, April.
  • Handle: RePEc:eee:csdana:v:45:y:2004:i:3:p:389-421
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(03)00035-5
    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. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    2. Neuenschwander, Beat E. & Flury, Bernard D., 1997. "A note on Silvey's (1959) Theorem," Statistics & Probability Letters, Elsevier, vol. 36(3), pages 307-317, 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. Iliopoulos, G. & Kateri, M. & Ntzoufras, I., 2007. "Bayesian estimation of unrestricted and order-restricted association models for a two-way contingency table," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4643-4655, May.
    2. Lu, Cheng & Teng, Da & Chen, Jun-Yu & Fei, Cheng-Wei & Keshtegar, Behrooz, 2023. "Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 234(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. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    2. Carvalho Lopes, Celia Mendes & Bolfarine, Heleno, 2012. "Random effects in promotion time cure rate models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 75-87, January.
    3. Neusser, Klaus, 2016. "A topological view on the identification of structural vector autoregressions," Economics Letters, Elsevier, vol. 144(C), pages 107-111.
    4. Chrysanthos Dellarocas & Charles A. Wood, 2008. "The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias," Management Science, INFORMS, vol. 54(3), pages 460-476, March.
    5. Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney K. Newey, 2014. "Local Identification of Nonparametric and Semiparametric Models," Econometrica, Econometric Society, vol. 82(2), pages 785-809, March.
    6. Tarpey, Thaddeus, 2000. "Parallel Principal Axes," Journal of Multivariate Analysis, Elsevier, vol. 75(2), pages 295-313, November.
    7. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    8. 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.
    9. Andrew Chesher & Adam Rosen, 2015. "Characterizations of identified sets delivered by structural econometric models," CeMMAP working papers 63/15, Institute for Fiscal Studies.
    10. Zirogiannis, Nikolaos & Tripodis, Yorghos, "undated". "A Generalized Dynamic Factor Model for Panel Data: Estimation with a Two-Cycle Conditional Expectation-Maximization Algorithm," Working Paper Series 142752, University of Massachusetts, Amherst, Department of Resource Economics.
    11. Dengdeng Yu & Matthew Pietrosanu & Ivan Mizera & Bei Jiang & Linglong Kong & Wei Tu, 2025. "Functional Linear Partial Quantile Regression with Guaranteed Convergence for Neuroimaging Data Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(1), pages 174-190, April.
    12. Luis Alvarez & Cristine Pinto & Vladimir Ponczek, 2022. "Homophily in preferences or meetings? Identifying and estimating an iterative network formation model," Papers 2201.06694, arXiv.org, revised Mar 2026.
    13. Matthew Read, 2023. "Estimating the Effects of Monetary Policy in Australia Using Sign‐restricted Structural Vector Autoregressions," The Economic Record, The Economic Society of Australia, vol. 99(326), pages 329-358, September.
    14. Tito Belchior Silva Moreira & Benjamin Miranda Tabak & Mario Jorge Mendonça & Adolfo Sachsida, 2016. "An Evaluation of the Non-Neutrality of Money," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-20, March.
    15. Hsiao, Cheng & Fujiki, Hiroshi, 1998. "Nonstationary Time-Series Modeling versus Structural Equation Modeling: With an Application to Japanese Money Demand," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 16(1), pages 57-79, May.
    16. Attanasio, Orazio & Cattan, Sarah & Fitzsimons, Emla & Meghir, Costas & Rubio-Codina, Marta, 2015. "Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia," IZA Discussion Papers 8856, IZA Network @ LISER.
    17. Mark P Little & Wolfgang F Heidenreich & Guangquan Li, 2009. "Parameter Identifiability and Redundancy in a General Class of Stochastic Carcinogenesis Models," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-6, December.
    18. Escanciano, Juan Carlos & Hoderlein, Stefan & Lewbel, Arthur & Linton, Oliver & Srisuma, Sorawoot, 2021. "Nonparametric Euler Equation Identification And Estimation," Econometric Theory, Cambridge University Press, vol. 37(5), pages 851-891, October.
    19. Raffaella Giacomini & Toru Kitagawa, 2021. "Robust Bayesian Inference for Set‐Identified Models," Econometrica, Econometric Society, vol. 89(4), pages 1519-1556, July.
    20. Zadrozny, Peter A., 2022. "Linear identification of linear rational-expectations models by exogenous variables reconciles Lucas and Sims," CFS Working Paper Series 682, Center for Financial Studies (CFS).

    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:45:y:2004:i:3:p:389-421. 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.