Predictions in Time Series Using Regression Models
(Sprache: Englisch)
This book will interest and assist people who are dealing with the problems of predictions of time series in higher education and research. It will greatly assist people who apply time series theory to practical problems in their work and also serve as a...
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This book will interest and assist people who are dealing with the problems of predictions of time series in higher education and research. It will greatly assist people who apply time series theory to practical problems in their work and also serve as a textbook for postgraduate students in statistics economics and related subjects.
Klappentext zu „Predictions in Time Series Using Regression Models “
This book deals with the statistical analysis of time series and covers situations that do not fit into the framework of stationary time series, as described in classic books by Box and Jenkins, Brockwell and Davis and others. Estimators and their properties are presented for regression parameters of regression models describing linearly or nonlineary the mean and the covariance functions of general time series. Using these models, a cohesive theory and method of predictions of time series are developed. The methods are useful for all applications where trend and oscillations of time correlated data should be carefully modeled, e.g., ecology, econometrics, and finance series. The book assumes a good knowledge of the basis of linear models and time series.
Inhaltsverzeichnis zu „Predictions in Time Series Using Regression Models “
Basic Mathematics and Statistics Random Processes and Time Series Estimation of Time Series Parameters Predictions in Time Series Empirical Predictors
Bibliographische Angaben
- Autor: Frantisek Stulajter
- 2002, 233 Seiten, Maße: 23,5 cm, Gebunden, Englisch
- Verlag: Springer, New York
- ISBN-10: 0387953507
- ISBN-13: 9780387953502
Sprache:
Englisch
Rezension zu „Predictions in Time Series Using Regression Models “
From the reviews: MATHEMATICAL REVIEWS "The book is useful for students and researchers of mathematical statistics, economical and financial mathematics and management with an important mathematical focus."
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