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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
Languages
R
Concepts
Data Analysis
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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.
Read more about Rami Krispin

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Date and time objects in R

The base package, one of R's core packages, provides two types of date and time classes:

  1. Date: This is a simple representation of a calendar date following the ISO 8601 international standard format (or the Gregorian calendar format) using the YYYY-m-d date format. Each date object has a numeric value of the number of days since the origin point (the default setting is 1970-01-01). In the Handling numeric date objects section in this chapter, we will discuss the usage of the origin in the reformatting process of date objects in more detail. It will make sense to use this format when the frequency of the data is daily or lower (for example, monthly, quarterly, and so on) and the time of the day doesn't matter.
  2. POSIXct/POSIXlt: Also known as the DateTime classes (that is, they represent both date and time), these are two POSIX date/time classes...
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Hands-On Time Series Analysis with R
Published in: May 2019Publisher: PacktISBN-13: 9781788629157
© 2019 Packt Publishing Limited All Rights Reserved

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

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