Time Series Regression and Exploratory Data Analysis

Part of the Springer Texts in Statistics book series (STS)


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.


Unbiased Estimator ARIMA Model Exploratory Data Analysis Autocovariance Function Nonstationary Time Series 
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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of California, DavisDavisUSA
  2. 2.Department of StatisticsUniversity of PittsburghPittsburghUSA

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