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Asymptotic Theory of Statistical Inference for Time Series

11 View(s), published at 2012-10-23, written by Masanobu Taniguchi, Yoshihide Kakizawa, published by Springer
Asymptotic Theory of Statistical Inference for Time Series

Asymptotic theory of statistical inference for time series by Masanobu Taniguchi, Yoshihide Kakizawa The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual AR, MA, and ARMA p.... Published date on: 2012-10-23 with total page: 662 pages. Publisher of Asymptotic Theory of Statistical Inference for Time Series is Springer.

The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual AR, MA, and ARMA processes. A wide variety of stochastic processes, including non-Gaussian linear processes, long-memory processes, nonlinear processes, non-ergodic processes and diffusion processes are described. The authors discuss estimation and testing theory and many other relevant statistical methods and techniques.

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