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Time Series Analysis

In: Supply Chain Engineering

Author

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  • Marc Goetschalckx

    (Georgia Institute of Technology)

Abstract

Recall that in the previous chapter objective or quantitative forecasting methods were defined as forecasting methods that rely on a formalized underlying model to make predictions. They are further divided into time series and causal methods. Time series analysis is a forecasting method based on the fundamental assumption that future estimates are based on prior, historical values of the same variable. This implies that the historical pattern exhibited by the variable to be forecasted will extend into the future. In addition, it is implicitly assumed that historical data are available. The only independent variable in a forecasting model based on time series analysis is the time period. Time series forecasting methods are mostly used to forecast variables for the short to intermediate term. As such, time series methods are some of the forecasting techniques most often used by logisticians and are developed in further detail in this chapter.

Suggested Citation

  • Marc Goetschalckx, 2011. "Time Series Analysis," International Series in Operations Research & Management Science, in: Supply Chain Engineering, chapter 0, pages 75-126, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-6512-7_4
    DOI: 10.1007/978-1-4419-6512-7_4
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