rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Time series analysis and its applications
    sub title: With R examples
  name:
    name part: Shumway, Robert H
    role:
      role term: creator
    role:
      role term: author
  name:
    name part: Stoffer, David S
    role:
      role term: author
  origin info:
    place:
      place term: Cham, Switzerland
    publisher: Springer
    date issued: 2017
    edition: Fourth Edition.
  language:
    language term: | 0
  physical description:
    form: electronic resource
    extent: xiii, 562 páginas. Online resource.
  abstract: The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods. This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.
  note: GC 20221018
  subject:
    topic: Estadística matemática
    topic: Tiempo y frecuencia
    genre: Análisis de series
  subject:
    topic: Análisis de series temporales
    genre: Métodos estadísticos
  classification: 519.55 SHU 2017
  identifier: 978-3-319-52451-1 (Softcover)
  identifier: 978-3-319-52452-8 (eBook)
  identifier: https://doi.org/10.1007/978-3-319-52452-8
  record info:
    record creation date: 221018
    record change date: 20241030161834.0