The data preprocessing does not complete once the series is transformed into a ts object because, in many cases, you may be required to apply some additional transformation or preprocessing steps. This includes steps such as extracting or subsetting a specific element of the series or aggregating the series to a different frequency (for example, from monthly to quarterly). A typical example of such a step is splitting the series into training and testing partitions when training a forecasting model. Due to the unique structure of the ts object, in most cases, the common extraction methods for data.frame do not apply to ts objects. In this section, we will introduce methods and designated functions for data manipulation of ts objects by using the window, aggregate, and other functions.
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You're reading from Hands-On Time Series Analysis with R
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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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