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You're reading from  R Statistics Cookbook

Product typeBook
Published inMar 2019
Reading LevelExpert
PublisherPackt
ISBN-139781789802566
Edition1st Edition
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Author (1)
Francisco Juretig
Francisco Juretig
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Francisco Juretig

Francisco Juretig has worked for over a decade in a variety of industries such as retail, gambling and finance deploying data-science solutions. He has written several R packages, and is a frequent contributor to the open source community.
Read more about Francisco Juretig

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Seasonality and SARIMAX models

In general, we will work with either quarterly, monthly, or weekly data. This is particularly interesting, because data arising from the same quarter/month/week will exhibit seasonal patterns. For example, if we are working with monthly sales of toys, we will see that they are usually bought in December as gifts. In consequence, all the data points related to December will be correlated. Seasonality terms have associated P/Q terms, which are analogous to their nonseasonal p/q counterparts.

Getting ready

In order to run this recipe, you will need to install the forecast package via install.packages("forecast").

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R Statistics Cookbook
Published in: Mar 2019Publisher: PacktISBN-13: 9781789802566

Author (1)

author image
Francisco Juretig

Francisco Juretig has worked for over a decade in a variety of industries such as retail, gambling and finance deploying data-science solutions. He has written several R packages, and is a frequent contributor to the open source community.
Read more about Francisco Juretig