Multivariate regression estimation local polynomial fitting for time series
نویسندگان
چکیده
منابع مشابه
Multivariate Regression Estimation : Local Polynomial Fitting for Time Series
We consider the estimation of the multivariate regression function m (x 1 , . . . ,xd) = E [ψ (Yd) | X 1 = x 1 , . . . ,Xd = xd], and its partial derivatives, for stationary random processes {Yi ,Xi} using local higher-order polynomial fitting. Particular cases of ψ yield estimation of the conditional mean, conditional moments and conditional distributions. Joint asymptotic normality is establi...
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Local high-order polynomial fitting is employed for the estimation of the multivariate regression function m (x 1 , . . . ,xd) = E [ψ (Yd) | X 1 = x 1 , . . . ,Xd = xd], and of its partial derivatives, for stationary random processes {Yi , Xi}. The function ψ may be selected to yield estimates of the conditional mean, conditional moments and conditional distributions. Uniform strong consistency...
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Estimation of a nonparametric regression spectrum based on the periodogram is considered. Neither trend estimation nor smoothing of the periodogram are required. Alternatively, for cases where spectral estimation of phase shifts fails and the shift does not depend on frequency, a time domain estimator of the lag-shift is defined. Asymptotic properties of the frequency and time domain estimators...
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ژورنال
عنوان ژورنال: Stochastic Processes and their Applications
سال: 1996
ISSN: 0304-4149
DOI: 10.1016/s0304-4149(96)00095-6