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Multivariate Probability Density and Regression Functions Estimation of Continuous-Time Stationary Processes from Discrete-Time Data

  • Elias Masry
Part of the Trends in Mathematics book series (TM)

Abstract

Let be a real-valued continuous-time jointly stationary processes and let tj be a renewal point process on [0,00], with finite mean rate independent of (Y,X). Given the observations and a measurable function, we estimate the multivariate probability density and the regression function of given X(0) = xo, X(T) = XI, …, X(r m ) = x m for arbitrary lags m. We present consistency and asymptotic normality results for appropriate estimates of f and r.

Keywords

Regression Function Asymptotic Normality Asymptotic Normality Result Local Polynomial Fitting Multivariate Probability Density 
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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Elias Masry
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of California, San DiegoLa JollaUSA

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