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Exploring Lagged Effects in Time Series

  • Nicolau A
  • Dyson K
  • Saah D
  • et al.
Springer International Publishing, (2024), 403-420
DOI: 10.1007/978-3-031-26588-4_21
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Abstract

Abstract: In this chapter, we will introduce lagged effects to build on the previous work in modeling time series data. Time-lagged effects occur when an event at one point in time impacts dependent variables at a later point in time. You will be introduced to concepts of autocovariance and autocorrelation, cross-covariance and cross-correlation, and auto-regressive models. At the end of this chapter, you will be able to examine how variables relate to one another across time and to fit time series models that take into account lagged events.

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APA

Nicolau, A. P., Dyson, K., Saah, D., & Clinton, N. (2024). Exploring Lagged Effects in Time Series. In Cloud-Based Remote Sensing with Google Earth Engine (pp. 403–420). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_21

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