Time Series Analysis is written for the traditional statistician who lacks the rigorous mathematical background required to use nonstationary time series methods. This practical, accessible volume:
- Offers statisticians the first comprehensive guide to nonstationary and noninvertible time series analysis
- Interprets and explains nonstationary time series from an exclusively statistical point of view
- Features over 90 illustrations and 50 tables that help clarify each technical point covered
- Provides helpful problems and solutions at the end of each section
Offering in–depth coverage of a mathematically rigorous topic in terms that statisticians can understand, Time Series Analysis is an indispensable reference for researchers and graduate students in econometrics, statistics, probability, actuarial science, and engineering.
Stochastic Calculus in Mean Square.
Functional Central Limit Theorems.
The Stochastic Process Approach.
The Fredholm Approach.
Estimation Problems in Nonstationary Autoregressive Models.
Estimation Problems in Noninvertible Moving Average Models.
Unit Root Tests in Autoregressive Models.
Unit Root Tests in Moving Average Models.
Statistical Analysis of Cointegration.
Solutions to Problems.
List of Series Titles.