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Characteristics of Time Series

  • Robert H. Shumway
  • David S. Stoffer
Chapter
Part of the Springer Texts in Statistics book series (STS)

Abstract

The analysis of experimental data that have been observed at different points in time leads to new and unique problems in statistical modeling and inference. The obvious correlation introduced by the sampling of adjacent points in time can severely restrict the applicability of the many conventional statistical methods traditionally dependent on the assumption that these adjacent observations are independent and identically distributed. The systematic approach by which one goes about answering the mathematical and statistical questions posed by these time correlations is commonly referred to as time series analysis.

Keywords

Time Series Linear Process Stationary Time Series Autocovariance Function Joint Distribution Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Robert H. Shumway
    • 1
  • David S. Stoffer
    • 2
  1. 1.Department of StatisticsUniversity of California, DavisDavisUSA
  2. 2.Department of StatisticsUniversity of PittsburghPittsburghUSA

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