Introductory Time Series with R (Use R!)

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9780387886978: Introductory Time Series with R (Use R!)

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

From the Back Cover:

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 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.

About the Author:

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

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ISBN 10: 0387886974 ISBN 13: 9780387886978
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Descrizione libro Condizione libro: New. Brand New. US Edition Book. We do not ship to Military Addresses. Fast Shipping with Order Tracking. For Standard Shipping 7-8 business days & Expedite Shipping 4-6 business days, after shipping. Codice libro della libreria 0387886974-RMX

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Descrizione libro Springer-Verlag New York Inc., United States, 2009. Paperback. Condizione libro: New. Language: English . Brand New Book. 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 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. Codice libro della libreria AAU9780387886978

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Paul S.P. Cowpertwait, Andrew Metcalfe
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Descrizione libro Springer-Verlag New York Inc., United States, 2009. Paperback. Condizione libro: New. Language: English . Brand New Book. 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 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. Codice libro della libreria AAU9780387886978

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Paul S.P. Cowpertwait, Andrew V. Metcalfe
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ISBN 10: 0387886974 ISBN 13: 9780387886978
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Descrizione libro Springer New York 2009-06-09, Dordrecht |London, 2009. paperback. Condizione libro: New. Codice libro della libreria 9780387886978

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Descrizione libro Springer-Verlag New York Inc. Paperback. Condizione libro: new. BRAND NEW, Introductory Time Series with R, Paul S.P. Cowpertwait, Andrew Metcalfe, Rhasacommandlineinterfacethato?ersconsiderableadvantagesovermenu systemsintermsofe?ciencyandspeedoncethecommandsareknownandthe languageunderstood. However,thecommandlinesystemcanbedauntingfor the?rst-timeuser,sothereisaneedforconcisetextstoenablethestudentor analysttomakeprogresswithRintheirareaofstudy. Thisbookaimstoful?l thatneedintheareaoftimeseries toenablethenon-specialisttoprogress, atafairlyquickpace,toalevelwheretheycancon?dentlyapplyarangeof timeseriesmethodstoavarietyofdatasets. Thebookassumesthereader hasaknowledgetypicalofa?rst-yearuniversitystatisticscourseandisbased aroundlecturenotesfromarangeoftimeseriescoursesthatwehavetaught overthelasttwentyyears. Someofthismaterialhasbeendeliveredtopo- graduate?nancestudentsduringaconcentratedsix-weekcourseandwaswell received,soaselectionofthematerialcouldbemasteredinaconcentrated course,althoughingeneralitwouldbemoresuitedtobeingspreadovera completesemester. Thebookisbasedaroundpracticalapplicationsandgenerallyfollowsa similar format for each time series model being studied. First, there is an introductory motivational section that describes practical reasons why the modelmaybeneeded. Second,themodelisdescribedandde?nedinma- ematicalnotation. Themodelisthenusedtosimulatesyntheticdatausing Rcodethatcloselyre?ectsthemodelde?nitionandthen?ttedtothes- theticdatatorecovertheunderlyingmodelparameters. Finally,themodel is?ttedtoanexamplehistoricaldatasetandappropriatediagnosticplots given. By using R, the whole procedure can be reproduced by the reader, 1 anditisrecommendedthatstudentsworkthroughmostoftheexamples. Mathematical derivations are provided in separate frames and starred sec- 1 WeusedtheRpackageSweavetoensurethat,ingeneral,yourcodewillproduce thesameoutputasours. However,forstylisticreasonswesometimeseditedour code;e. g. ,fortheplotstherewillsometimesbeminordi?erencesbetweenthose generatedbythecodeinthetextandthoseshownintheactual?gures. vii viii Preface tionsandcanbeomittedbythosewantingtoprogressquicklytopractical applications. Attheendofeachchapter,aconcisesummaryoftheRc- mands that were used is given followed by exercises. All data sets used in thebook,andsolutionstotheoddnumberedexercises,areavailableonthe websitehttp://www. massey. ac. nz/?pscowper/ts. WethankJohnKimmelofSpringerandtheanonymousrefereesfortheir helpfulguidanceandsuggestions,BrianWebbyforcarefulreadingofth etext andvaluablecomments,andJohnXieforusefulcommentsonanearlierdraft. TheInstituteofInformationandMathematicalSciencesatMasseyUniv- sity and the School of Mathematical Sciences, University of Adelaide, are acknowledgedforsupportandfundingthatmadeourcollaborationpossible. Paul thanks his wife, Sarah, for her continual encouragement and support duringthewritingofthisbook,andourson,Daniel,anddaughters,Lydia andLouise,forthejoytheybringtoourlives. AndrewthanksNataliefor providinginspirationandherenthusiasmfortheproject. PaulCowpertwaitandAndrewMetcalfe MasseyUniversity,Auckland,NewZealand UniversityofAdelaide,Australia December2008 Contents Preface.vii 1 TimeSeriesData.1 1. 1 Purpose.1 1. 2 Timeseries.2 1. 3 Rlanguage.3 1. 4 Plots,trends,andseasonalvariation .4 1. 4. 1 A?yingstart:Airpassengerbookings.4 1. 4. 2 Unemployment:Maine.7 1. 4. 3 Multipletimeseries:Electricity,beerandchocolatedata 10 1. 4. 4 Quarterlyexchangerate:GBPtoNZdollar.14 1. 4. 5 Globaltemperatureseries .16 1. 5 Decompositionofseries .19 1. 5. 1 Notation.19 1. 5. 2 Models.1 9 1. 5. 3 Estimatingtrendsandseasonale?ects .20 1. 5. 4 Smoothing .21 1. 5. 5 DecompositioninR.22 1. 6 Summaryofcommandsusedinexamples.24 1. 7 Exercises.24 2 Correlation.27 2. 1 Purpose.27 2. 2 Expectationandtheensemble. Codice libro della libreria B9780387886978

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Descrizione libro Springer-Verlag New York Inc., 2009. PAP. Condizione libro: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria IQ-9780387886978

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Descrizione libro Springer, 2009. Condizione libro: New. This book gives the reader a step-by-step introduction to analyzing time series using the open source software R. Each time series model is illustrated through practical applications addressing contemporary issues, and is defined in mathematical notation. Series: Use R! Num Pages: 256 pages, biography. BIC Classification: PBT. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 232 x 158 x 15. Weight in Grams: 388. . 2009. 2009th Edition. Paperback. . . . . . Codice libro della libreria V9780387886978

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Descrizione libro Springer, 2009. Paperback. Condizione libro: New. 2009. This item is printed on demand. Codice libro della libreria DADAX0387886974

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Descrizione libro Springer. Condizione libro: New. This book gives the reader a step-by-step introduction to analyzing time series using the open source software R. Each time series model is illustrated through practical applications addressing contemporary issues, and is defined in mathematical notation. Series: Use R! Num Pages: 256 pages, biography. BIC Classification: PBT. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 232 x 158 x 15. Weight in Grams: 388. . 2009. 2009th Edition. Paperback. . . . . Books ship from the US and Ireland. Codice libro della libreria V9780387886978

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Descrizione libro Springer, 2009. Condizione libro: New. book. Codice libro della libreria ria9780387886978_rkm

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