Higher Order Asymptotic Theory for Time Series Analysis

The initial basis of this book was a series of my research papers, that I listed in References. I have many people to thank for the book's existence. Regarding higher order asymptotic efficiency I thank Professors Kei Takeuchi and M. Akahira for their many comments. I used their concept of effi...

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Bibliographic Details
Main Author: Taniguchi, Masanobu
Format: eBook
Language:English
Published: New York, NY Springer New York 1991, 1991
Edition:1st ed. 1991
Series:Lecture Notes in Statistics
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 1 A Survey of the First-Order Asymptotic Theory for Time Series Analysis
  • 2 Higher Order Asymptotic Theory for Gaussian Arma Processes
  • 2.1. Higher order asymptotic efficiency and Edgeworth expansions
  • 2.2. Second-order asymptotic efficiency for Gaussian ARMA processes
  • 2.3. Third-order asymptotic efficiency for Gaussian ARMA processes
  • 2.4. Normalizing transformations of some statistics of Gaussian ARMA processes
  • 2.5. Higher order asymptotic efficiency in time series regression models
  • 3 Validity of Edgeworth Expansions in Time Series Analysis
  • 3.1. Berry-Esseen theorems for quadratic forms of Gaussian stationary processes
  • 3.2. Validity of Edgeworth expansions of generalized maximum likelihood estimators for Gaussian ARMA processes
  • 4 Higher Order Asymptotic Sufficiency, Asymptotic Ancillarity in Time Series Analysis
  • 4.1. Higher order asymptotic sufficiency for Gaussian ARMA processes
  • 4.2. Asymptotic ancillarity in time series analysis
  • 5 Higher Order Investigations for Testing Theory in Time Series Analysis
  • 5.1. Asymptotic expansions of the distributions of a class of tests under the null hypothesis
  • 5.2. Comparisons of powers of a class of tests under a local alternative
  • 6 Higher Order Asymptotic Theory for Multivariate Time Series
  • 6.1. Asymptotic expansions of the distributions of functions of the eigenvalues of sample covariance matrix in multivariate time series
  • 6.2. Asymptotic expansions of the distributions of functions of the eigenvalues of canonical correlation matrix in multivariate time series
  • 7 Some Practical Examples
  • References
  • Author Index