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  <titleInfo>
    <title>Introductory time series with R</title>
  </titleInfo>
  <name type="personal">
    <namePart>Paul S P Cowpertwait ; Andrew V Metcalfe</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart> Andrew V Metcalfe</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="">Time-series analysis--Computer programs-Mathematical statistics</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">xxu</placeTerm>
    </place>
    <place>
      <placeTerm type="text">New York</placeTerm>
    </place>
    <publisher> : Springer-Verlag</publisher>
    <dateIssued>, ©2009</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xv,254 Pages ;24 cm.</extent>
  </physicalDescription>
  <abstract>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.</abstract>
  <tableOfContents>1.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
</tableOfContents>
  <note type="statement of responsibility">/Paul S P Cowpertwait</note>
  <subject>
    <topic>R (Computer program language)</topic>
  </subject>
  <classification authority="ddc">519.2 COW</classification>
  <identifier type="isbn">9780387886978</identifier>
  <identifier type="">SARAS Books ;2/31,Ansari Road,Darya Ganj,New Delhi-110002</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">180926</recordCreationDate>
    <recordChangeDate encoding="iso8601">20181102112211.0</recordChangeDate>
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