Akaike H., Kitagawa G. (eds.) The Practice of Time Series Analysis

New York: Springer, 1999. — 387 p.Due to the introduction of the information criterion AIC and development of prac­ tical use of Bayesian modeling, the method of time analysis is now showing remarkable progress. In attempting the study of a new field the actual phenomenon is rarely so simple as to allow direct applications of existing methods of analysis or models. The real thrill of the statistical analysis lies in the process of developing a new model depending on the purpose and the characteristics of the object of the research. The purpose of this book ist.o introduce the readers to successful applications of the meth­ ods of time series analysis in a variety of fields, such as engineering, earth science, medical science, biology, and economics. The editors have been aware of the importance of cooperative research in sta­ tistical science and carried out various cooperative research projects in the area of time series analysis. The Institute of Statistical Mathematics was reorganized as an inter-university research institute in 1985 and the activities of the Institute have been organized to promote the cooperative researches as its central activity. This book is composed of the outcomes of cooperative researches developed within this environ­ ment and contains the results ranging from the pioneering realizations of statistical control to the latest consequences of time series modeling.Control of Boilers for Thermoelectric Power Plants by Means of a Statistical Model
Feedback Analysis of a Living Body by a Multivariate Autoregressive Model
Factor Decomposition of Economic Time Series Fluctuations — Economic and statistical models in harmony —
The Statistical Optimum Control of Ship Motion and a Marine Main Engine
High Precision Estimation of Seismic Wave Arrival Times
Analysis of Dynamic Characteristics of a Driver-Vehicle System
Estimation of Directional Wave Spectra Using Ship Motion Data
Control of Filature Production Process
Application to Pharmacokinetic Analysis
State Space Modeling of Switching Time Series
Time Varying Coefficient AR and VAR Models
Statistical Control of Cement Process
Analysis of a Human/2-wheeled-Vehicle System by ARdock
Vibration Data Analysis of Automobiles
Auto-regressive Spectral Analysis of RR-Interval Time Series in Healthy Fetus and Newborn Infants
Information Processing Mechanisms in the Mammalian Brain: Analysis of Spatio-temporal Neural Response in the Auditory Cortex
Time Series Analysis of Financial Asset Price Fluctuations
Dynamic Analysis of Economic Time Series
Processing of Time Series Data Obtained by Satellites
Analysis of Earth Tides Data
Detection of Groundwater Level Changes Related to Earthquakes
Processing of Missing Observations and Outliers in Time Series
Mental Preparation for Time Series Analysis