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008			150903s2009 xxu| o |||| 0|eng d
020			_a9780387886985 _99780387886985
024	7		_a10.1007/9780387886985 _2doi
035			_avtls000333246
039		9	_a201509030227 _bVLOAD _c201404130402 _dVLOAD _c201404092151 _dVLOAD _y201402041106 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
100	1		_aMetcalfe, Andrew V. _eautor _9305779
245	1	0	_aIntroductory Time Series with R / _cby Andrew V. Metcalfe, Paul S.P. Cowpertwait.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_axvI, 256 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aUse R
500			_aSpringer eBooks
505	0		_aTime 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.
520			_aYearly 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 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. 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.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aCowpertwait, Paul S.P. _eautor _9305780
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387886978
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-88698-5 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c280684 _d280684