000			02051nam a22002417a 4500
005			20181102112211.0
008			180926b xxu||||| |||| 00| 0 eng d
020			_a9780387886978
028			_aSARAS Books _b;2/31,Ansari Road,Darya Ganj,New Delhi-110002 _c;IN37761 _d;21/09/2018
082			_a519.2 COW
100			_aPaul S P Cowpertwait _a; Andrew V Metcalfe
245			_aIntroductory time series with R _c/Paul S P Cowpertwait
260			_aNew York _b : Springer-Verlag _c, ©2009.
300			_axv,254 Pages _c;24 cm.
365			_b1844
490			_aUse R!
505			_a1.Time Series Data 2.Correlation 3.Forecasting Strategies 4.Basic Stochastic Models 5.Regression 6.Stationary Models 7.Non-Stationary Model 8.Long Memory Processes 9.Spectral Analysis 10.System Identification 11.Multivariate Models 12.State Space Models
520			_aThis 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 for undergraduate 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.
650			_aR (Computer program language)
655			_aTime-series analysis--Computer programs _bMathematical statistics
700			_a Andrew V Metcalfe
942			_cBOOK
999			_c50304 _d50304