Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes
نویسندگان
چکیده
منابع مشابه
Nonlinear Wavelet Estimation of Time-varying Autoregressive Processes
We consider nonparametric estimation of the parameter functions a i () , i = 1; : : : ; p , of a time-varying autoregressive process. Choosing an orthonormal wavelet basis representation of the functions a i , the empirical wavelet coeecients are derived from the time series data as the solution of a least squares minimization problem. In order to allow the a i to be functions of inhomogeneous ...
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R A I N E R DA H L H AU S , 1 M I C H A E L H . N E U M A N N 2 and RAINER VON SACHS 3 Institut fuÈ r Angewandte Mathematik, UniversitaÈ t Heidelberg, Im Neuenheimer Feld 294, D-69120 Heidelberg, Germany. E-mail: [email protected] SFB 373, Humboldt-UniversitaÈ t zu Berlin, Spandauer Strasse 1, D-10178 Berlin, Germany. E-mail: [email protected] Institut de Statistique, U...
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Parameter estimation of time-varying non-Gaussian autoregressive processes can be a highly nonlinear problem. The problem gets even more difficult if the functional form of the time variation of the process parameters is unknown. In this paper, we address parameter estimation of such processes by particle filtering, where posterior densities are approximated by sets of samples (particles) and p...
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ژورنال
عنوان ژورنال: Bernoulli
سال: 1999
ISSN: 1350-7265
DOI: 10.2307/3318448