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Tytuł artykułu

The Fisher information and exponential families parametrized by a segment of means

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Języki publikacji
EN
Abstrakty
EN
We consider natural and general exponential families (Qm)mϵM on Rd parametrized by the means. We study the submodels (Q0m1+(1−0)m2)0ϵ[0, 1] parametrized by a segment in the means domain from the point of view of the Fisher information. Such a parametrization allows for a parsimonious model and is particularly useful in practical situations when hesitating between two parameters m1 and m2. The most interesting cases are multivariate Gaussian and Wishart models with matrix parameters.
Rocznik
Strony
73--90
Opis fizyczny
Bibliogr. 16 poz.
Twórcy
autor
  • LAREMA, Université d’Angers, 2 Bd Lavoisier, 49045 Angers Cedex 01, France
autor
  • School of Statistics and Actuarial Science, University of the Witwatersrand
  • LAREMA, Université d’Angers, Private Bag x3, Wits 2050, South Africa
Bibliografia
  • [1] T. Andersson and P. Händel, IEEE Standard 1057. Cramér-Rao bound and the parsimony principle, IEEE Transactions on Instrumentation and Measurement 55 (1) (2006), pp. 44-53.
  • [2] J.-F. Bercher and C. Vignat, On minimum Fisher information distributions with restricted support and fixed variance, Inform. Sci. 179 (2009), pp. 3832-3842.
  • [3] G. Casella and R. L. Berger, Statistical Inference, Duxbury Advances Series, 2002.
  • [4] J. Faraut and A. Korányi, Analysis on Symmetric Cones, Oxford Math. Monogr., Oxford University Press, New York 1994.
  • [5] R. M. Gray, Toeplitz and Circulant Matrices: A review, Foundations and Trends in Communications and Information Theory, Vol. 2, Issue 3, NOW Publishers, 2006, pp. 155-239.
  • [6] R. D. Gupta and D. Kundu, On the comparison of Fisher information of the Weibull and GE distributions, J. Statist. Plann. Inference 136 (2006), pp. 3130-3144.
  • [7] E. L. Lehmann and G. Casella, Theory of Point Estimation, Springer Texts Statist., Springer, New York 1998.
  • [8] E. L. Lehmann and J. P. Romano, Testing Statistical Hypotheses, Springer Texts Statist., Springer, New York 2005.
  • [9] G. Letac, Lectures on Natural Exponential Families and Their Variance Functions, Monogr. Mat., Vol. 50, IMPA, Rio de Janeiro 1992.
  • [10] G. Letac and M. Casalis, Natural exponential families, in: Continuous Multivariate Distributions. Volume 1: Models and Applications, second edition, S. Klotz, N. Balakrishnan, and N. L. Johnson (Eds.), Wiley Ser. Probab. Stat., 2000.
  • [11] G. Letac and H. Massam, The noncentral Wishart as an exponential family, and its moments, J. Multivariate Anal. 99 (7) (2008), pp. 1393-1417.
  • [12] G. Letac and H. Massam, Existence and non-existence of the noncentral Wishart distributions, preprint, 2011.
  • [13] J. R. Magnus and H. Neudecker, Matrix Differential Calculus with Applications in Statistics and Econometrics, Wiley, 2007.
  • [14] J. C. Mason and D. C. Handscomb, Chebyshev Polynomials, Chapman & Hall/CRC, 2003.
  • [15] R. J. Muirhead, Aspects of Multivariate Statistical Theory, Wiley, Hoboken, New Jersey, 2005.
  • [16] V. Rico-Ramirez, P. A. Quintana-Hernandez, S. Hernandez-Castro, and U. M. Diwekar, Fisher information as a novel tool for process control applications, in: 20th European Symposium on Computer Aided Process Engineering – ESCAPE20, S. Pierucci and G. Buzzi Ferraris (Eds.), Elsevier B. V., 2010.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-53fdf204-f42b-4c71-bc96-9ebd50ec048d
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