IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v32y1985i1p275-292.html
   My bibliography  Save this article

A dual approach for matrix-derivatives

Author

Listed:
  • W. Polasek

Abstract

No abstract is available for this item.

Suggested Citation

  • W. Polasek, 1985. "A dual approach for matrix-derivatives," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 32(1), pages 275-292, December.
  • Handle: RePEc:spr:metrik:v:32:y:1985:i:1:p:275-292
    DOI: 10.1007/BF01897818
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF01897818
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/BF01897818?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. Leamer, Edward E, 1972. "A Class of Informative Priors and Distributed Lag Analysis," Econometrica, Econometric Society, vol. 40(6), pages 1059-1081, November.
    2. Magnus, J.R. & Neudecker, H., 1979. "The commutation matrix : Some properties and applications," Other publications TiSEM d0b1e779-7795-4676-ac98-1, Tilburg University, School of Economics and Management.
    Full references (including those not matched with items on IDEAS)

    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. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Research Discussion Papers 4/1991, Bank of Finland.
    2. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    3. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "How Sensitive Are VAR Forecasts to Prior Hyperparameters? An Automated Sensitivity Analysis," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 229-248, Emerald Group Publishing Limited.
    4. O. J. Boxma & E. J. Cahen & D. Koops & M. Mandjes, 2019. "Linear Stochastic Fluid Networks: Rare-Event Simulation and Markov Modulation," Methodology and Computing in Applied Probability, Springer, vol. 21(1), pages 125-153, March.
    5. Loperfido, Nicola, 2014. "Linear transformations to symmetry," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 186-192.
    6. Liu, Shuangzhe & Leiva, Víctor & Zhuang, Dan & Ma, Tiefeng & Figueroa-Zúñiga, Jorge I., 2022. "Matrix differential calculus with applications in the multivariate linear model and its diagnostics," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    7. Arismendi, J.C., 2013. "Multivariate truncated moments," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 41-75.
    8. Reinaldo B. Arellano-Valle & Adelchi Azzalini, 2022. "Some properties of the unified skew-normal distribution," Statistical Papers, Springer, vol. 63(2), pages 461-487, April.
    9. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Tests for Random Coefficient Variation in Vector Autoregressive Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 1-35, Emerald Group Publishing Limited.
    10. Symeonides Spyridon D. & Karavias Yiannis & Tzavalis Elias, 2017. "Size corrected Significance Tests in Seemingly Unrelated Regressions with Autocorrelated Errors," Journal of Time Series Econometrics, De Gruyter, vol. 9(1), pages 1-41, January.
    11. Heinz Neudecker, 2004. "Problemsection," Statistical Papers, Springer, vol. 45(2), pages 297-301, April.
    12. Hausman, Jerry & Kuersteiner, Guido, 2008. "Difference in difference meets generalized least squares: Higher order properties of hypotheses tests," Journal of Econometrics, Elsevier, vol. 144(2), pages 371-391, June.
    13. L. J. Welty & R. D. Peng & S. L. Zeger & F. Dominici, 2009. "Bayesian Distributed Lag Models: Estimating Effects of Particulate Matter Air Pollution on Daily Mortality," Biometrics, The International Biometric Society, vol. 65(1), pages 282-291, March.
    14. Liu-Evans, Gareth, 2014. "A note on approximating moments of least squares estimators," MPRA Paper 57543, University Library of Munich, Germany.
    15. Jan Koláček & Ivana Horová, 2017. "Bandwidth matrix selectors for kernel regression," Computational Statistics, Springer, vol. 32(3), pages 1027-1046, September.
    16. Paul Bekker, 1986. "A note on the identification of restricted factor loading matrices," Psychometrika, Springer;The Psychometric Society, vol. 51(4), pages 607-611, December.
    17. Manuel Galea & Patricia Giménez, 2019. "Local influence diagnostics for the test of mean–variance efficiency and systematic risks in the capital asset pricing model," Statistical Papers, Springer, vol. 60(1), pages 293-312, February.
    18. Filippeli, Thomai & Harrison, Richard & Theodoridis, Konstantinos, 2018. "DSGE-based Priors for BVARs & Quasi-Bayesian DSGE Estimation," Cardiff Economics Working Papers E2018/5, Cardiff University, Cardiff Business School, Economics Section.
    19. Robert Boik, 2008. "Newton Algorithms for Analytic Rotation: an Implicit Function Approach," Psychometrika, Springer;The Psychometric Society, vol. 73(2), pages 231-259, June.
    20. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.

    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:spr:metrik:v:32:y:1985:i:1:p:275-292. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.