THÈSE Estimation, validation et identification des modèles ARMA ...

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Chapitre 5. Model selection of weak VARMA models 166 5.6 References Akaike, H. (1973) Information theory and an extension of the maximum likelihood principle. In 2nd International Symposium on Information Theory, Eds. B. N. Petrov and F. Csáki, pp. 267–281. Budapest : Akadémia Kiado. Boubacar Mainassara, Y. and Francq, C. (2009) Estimating structural VARMA models with uncorrelated but non-independent error terms. Working Papers, http ://perso.univ-lille3.fr/ cfrancq/pub.html. Brockwell, P. J. and Davis, R. A. (1991) Time series : theory and methods. Springer Verlag, New York. Dufour, J-M., and Pelletier, D. (2005) Practical methods for modelling weak VARMA processes : identification, estimation and specification with a macroeconomic application. Technical report, Département de sciences économiques and CIREQ, Université de Montréal, Montréal, Canada. Findley, D.F. (1993) The overfitting principles supporting AIC, Statistical Research Division Report RR 93/04, Bureau of the Census. Francq, C. and Raïssi, H. (2006) Multivariate Portmanteau Test for Autoregressive Models with Uncorrelated but Nonindependent Errors, Journal of Time Series Analysis 28, 454–470. Francq, C., Roy, R. and Zakoïan, J-M. (2005) Diagnostic checking in ARMA Models with Uncorrelated Errors, Journal of the American Statistical Association 100, 532–544. Francq, and Zakoïan, J-M. (1998) Estimating linear representations of nonlinear processes, Journal of Statistical Planning and Inference 68, 145–165. Francq, and Zakoïan, J-M. (2000) Covariance matrix estimation of mixing weak ARMA models, Journal of Statistical Planning and Inference 83, 369–394. Francq, and Zakoïan, J-M. (2005) Recent results for linear time series models with non independent innovations. In Statistical Modeling and Analysis for Complex Data Problems, Chap. 12 (eds P. Duchesne and B. Rémillard). New York : Springer Verlag, 137–161. Francq, and Zakoïan, J-M. (2007) HAC estimation and strong linearity testing in weak ARMA models, Journal of Multivariate Analysis 98, 114–144. Hannan, E. J. and Rissanen (1982) Recursive estimation of mixed of Autoregressive Moving Average order, Biometrika 69, 81–94. Hurvich, C. M. and Tsai, C-L. (1989) Regression and time series model selection in small samples. Biometrika 76, 297–307. Hurvich, C. M. and Tsai, C-L. (1993) A corrected Akaïke information criterion for vector autoregressive model selection. Journal of Time Series Analysis 14, 271–279. Lütkepohl, H. (1993) Introduction to multiple time series analysis. Springer Verlag, Berlin.
Chapitre 5. Model selection of weak VARMA models 167 Lütkepohl, H. (2005) New introduction to multiple time series analysis. Springer Verlag, Berlin. Magnus, J.R. and H. Neudecker (1988) Matrix Differential Calculus with Application in Statistics and Econometrics. New-York, Wiley. Reinsel, G. C. (1993) Elements of multivariate time series. Springer Verlag, New York. Reinsel, G. C. (1997) Elements of multivariate time series Analysis. Second edition. Springer Verlag, New York. Romano, J. L. and Thombs, L. A. (1996) Inference for autocorrelations under weak assumptions, Journal of the American Statistical Association 91, 590–600.
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UNIVERSITÉ CHARLES DE GAULLE - LIL
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Résumé Dans cette thèse nous él
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Abstract The goal of this thesis is
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Table des matières Résumé ii Abs
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4.6 Limiting distribution of the po
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4.12 Empirical size (in %) of the s
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Chapitre 1 Introduction Lorsque l
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Chapitre 1. Introduction 3 Pour les
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Chapitre 1. Introduction 5 VARMA(p0
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Chapitre 1. Introduction 7 obtenir
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Chapitre 1. Introduction 9 les outi
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Chapitre 1. Introduction 11 1.1.1 E
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Chapitre 1. Introduction 13 Propri
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Chapitre 1. Introduction 15 H7 : Po
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Chapitre 1. Introduction 17 Défini
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Chapitre 1. Introduction 19 où λ
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Chapitre 1. Introduction 21 Remarqu
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Chapitre 1. Introduction 23 où Eij
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Chapitre 1. Introduction 25 La dém
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Chapitre 1. Introduction 27 Théor
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Chapitre 1. Introduction 29 La sél
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Chapitre 1. Introduction 31 La dém
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Chapitre 1. Introduction 33 de BP d
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Chapitre 1. Introduction 35 Théor
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Chapitre 1. Introduction 37 Les exp
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Chapitre 1. Introduction 39 indispe
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Chapitre 1. Introduction 41 Lemme 1
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Chapitre 1. Introduction 43 En util
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Chapitre 1. Introduction 45 I11 = 2
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Chapitre 1. Introduction 47 ceux-ci
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Chapitre 1. Introduction 49 Remarqu
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Références bibliographiques Ahn,
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Chapitre 1. Introduction 53 Hannan,
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Chapitre 2 Estimating structural VA
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Chapitre 2. Estimating weak structu
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1(2, 2) − b ^ 1(2, 2) Density Cha
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THÈSE Estimation, validation et identification des modèles ARMA ...

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