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＜電子ブック＞
Introductory Time Series with R / by Paul S.P. Cowpertwait, Andrew V. Metcalfe
(Use R!. ISSN:21975744)

版	1st ed. 2009.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2009
本文言語	英語
大きさ	XVI, 256 p : online resource
著者標目	*Cowpertwait, Paul S.P author Metcalfe, Andrew V author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Statistics  LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Mathematical statistics LCSH:Marketing LCSH:Econometrics LCSH:Signal processing FREE:Probability Theory FREE:Statistical Theory and Methods FREE:Probability and Statistics in Computer Science FREE:Marketing FREE:Econometrics FREE:Signal, Speech and Image Processing
一般注記	Time Series Data -- Correlation -- Forecasting Strategies -- Basic Stochastic Models -- Regression -- Stationary Models -- Non-stationary Models -- Long-Memory Processes -- Spectral Analysis -- System Identification -- Multivariate Models -- State Space Models Yearly global mean temperature and ocean levels, daily share prices, and the signals transmitted back to Earth by the Voyager space craft are all examples of sequential observations over time known as time series. This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written forundergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research. Paul Cowpertwait is an associate professor in mathematical sciences (analytics) at Auckland University of Technology with a substantial research record in both the theory and applications of time series and stochastic models. Andrew Metcalfe is an associate professor in the School of Mathematical Sciences at the University of Adelaide, and an author of six statistics text books and numerous research papers. Both authors have extensive experience of teaching time series to students at all levels HTTP:URL=https://doi.org/10.1007/978-0-387-88698-5

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