Title : ( Multivariate Stochastic Regression Estimation by Wavelets for Stationary Time Series )
Authors: Hassan Doosti , Hossein Ali Niroumand ,
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Abstract
The estimation of multivariate stochastic regression for a stationary random process X_i using wavelet methods is considered. Uniform rates of almost sure convergence over compact subsets of d ℜ in the Besov space spq B are established for strongly mixing processes. Also, considering the case 1 d = , the results given by Doosti et al. (2008) are obtained as special cases.
Keywords
, Wavelet method, Besov Spaces; Rates of Strong Convergence; Strongly Mixing Processes; Nonparametric Curve Estimation; Probability Density Estimation
@article{paperid:1009664,
author = {Doosti, Hassan and Niroumand, Hossein Ali},
title = {Multivariate Stochastic Regression Estimation by Wavelets for Stationary Time Series},
journal = {Pakistan Journal of Statistics},
year = {2009},
volume = {27},
number = {1},
month = {January},
issn = {1012-9367},
pages = {37--46},
numpages = {9},
keywords = {Wavelet method; Besov Spaces; Rates of Strong Convergence; Strongly Mixing
Processes; Nonparametric Curve Estimation; Probability Density Estimation},
}
%0 Journal Article
%T Multivariate Stochastic Regression Estimation by Wavelets for Stationary Time Series
%A Doosti, Hassan
%A Niroumand, Hossein Ali
%J Pakistan Journal of Statistics
%@ 1012-9367
%D 2009
