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Time Series Regression and Exploratory Data Analysis

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

Abstract

In this chapter we introduce classical multiple linear regression in a time series context, model selection, exploratory data analysis for preprocessing nonstationary time series (for example trend removal), the concept of differencing and the backshift operator, variance stabilization, and nonparametric smoothing of time series.

Keywords

Unbiased Estimator ARIMA Model Exploratory Data Analysis Autocovariance Function Nonstationary Time Series 
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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