Time Series (Hardcover)
Language: English
Published by Oxford University Press, Oxford, 2024
- Hardcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
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Hardcover. Time series analysis is one of several branches of statistics whose practical importance has increased with the availability of powerful computational tools. Methodology that was originally developed for specialized applications, for example in finance or geophysics, is now widely available within general statistical packages.The second edition of Time Series: A Biostatistical Introduction is an introductory account of time series analysis, written from the perspective of applied statisticians whose interests lie primarily in the biomedical and health sciences. This edition has a stronger focus on substantive applications, in which each statistical analysis is directed at a specific research question. Separate chapters cover simple descriptive methods of analysis, including time-plots, smoothing, the correlogram and the periodogram; theory of stationary random processes; discrete-time models for single series; continuous-time models for single series; generalized linear models for time series of counts; models for replicated series; spectral analysis, and bivariate time series.The book is unique in its focus on biomedical and health science applications, which has been strengthened in this second edition. Nevertheless, the methods described are more widely applicable. It should be useful to teachers and students on masters-level degree courses in statistics, biostatistics and epidemiology, and to biomedical and health scientists with a knowledge of statistical methods at undergraduate level. Throughout, examples based on real datasets show a close interplay between statistical method and substantive science. This book will also describe the implementation of the methods in the R computing environment and provide access to R code and datasets. A time series is a sequence of measurements on a process whose future behaviour cannot be predicted exactly from past and current observations. This book focuses on applications in the biomedical and health and sciences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9780198714835
- Title
- Time Series (Hardcover)
- Author
- Prof Peter Diggle
- Publisher
- Oxford University Press, Oxford
- Publication year
- 2024
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0198714831
- ISBN 13
- 9780198714835
- Edition
- 2nd Edition
The second edition of Time Series: A Biostatistical Introduction is an introductory account of time series analysis, written from the perspective of applied statisticians whose interests lie primarily in the biomedical and health sciences. This edition has a stronger focus on substantive applications, in which each statistical analysis is directed at a specific research question. Separate chapters cover simple descriptive methods of analysis, including time-plots, smoothing, the correlogram and the periodogram; theory of stationary random processes; discrete-time models for single series; continuous-time models for single series; generalized linear models for time series of counts; models for replicated series; spectral analysis, and bivariate time series.
The book is unique in its focus on biomedical and health science applications, which has been strengthened in this second edition. Nevertheless, the methods described are more widely applicable. It should be useful to teachers and students on masters-level degree courses in statistics, biostatistics and epidemiology, and to biomedical and health scientists with a knowledge of statistical methods at undergraduate level. Throughout, examples based on real datasets show a close interplay between statistical method and substantive science. This book will also describe the implementation of the methods in the R computing environment and provide access to R code and datasets.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Emanuele Giorgi, a Lancaster University Ph.D. graduate in Statistics and Epidemiology (2015), is an Associate Professor in Biostatistics at the Lancaster Medical School. While leading the Centre for Health Informatics, Computing, and Statistics (CHICAS), he specializes in the development of spatial and spatio-temporal statistical methods and their application to tropical diseases epidemiology.
"About the title" may belong to another edition of this title.
Grand Eagle Retail
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