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You're reading from  Hands-On Time Series Analysis with R

Product typeBook
Published inMay 2019
Reading LevelBeginner
PublisherPackt
ISBN-139781788629157
Edition1st Edition
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Author (1)
Rami Krispin
Rami Krispin
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Rami Krispin

Rami Krispin is a data scientist at a major Silicon Valley company, where he focuses on time series analysis and forecasting. In his free time, he also develops open source tools and is the author of several R packages, including the TSstudio package for time series analysis and forecasting applications. Rami holds an MA in Applied Economics and an MS in actuarial mathematics from the University of MichiganAnn Arbor.
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Handling forecast uncertainty

The main goal of the forecasting process, as we saw previously, is to minimize the level of uncertainty around the future values of the series. Although we cannot completely eliminate this uncertainty, we can quantify it and provide some range around the point estimate of the forecast (which is nothing but the model's expected value of each point in the future). This can be done by using either the confidence interval (or a credible interval, when using the Bayesian model) or by using simulation.

Confidence interval

The confidence interval is a statistical approximation method that's used to express the range of possible values that contain the true value with some degree of confidence...

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Hands-On Time Series Analysis with R
Published in: May 2019Publisher: PacktISBN-13: 9781788629157

Author (1)

author image
Rami Krispin

Rami Krispin is a data scientist at a major Silicon Valley company, where he focuses on time series analysis and forecasting. In his free time, he also develops open source tools and is the author of several R packages, including the TSstudio package for time series analysis and forecasting applications. Rami holds an MA in Applied Economics and an MS in actuarial mathematics from the University of MichiganAnn Arbor.
Read more about Rami Krispin