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Hands-On Time Series Analysis with R

You're reading from   Hands-On Time Series Analysis with R Perform time series analysis and forecasting using R

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781788629157
Length 448 pages
Edition 1st Edition
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Author (1):
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Rami Krispin Rami Krispin
Author Profile Icon Rami Krispin
Rami Krispin
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Time Series Analysis and R 2. Working with Date and Time Objects FREE CHAPTER 3. The Time Series Object 4. Working with zoo and xts Objects 5. Decomposition of Time Series Data 6. Seasonality Analysis 7. Correlation Analysis 8. Forecasting Strategies 9. Forecasting with Linear Regression 10. Forecasting with Exponential Smoothing Models 11. Forecasting with ARIMA Models 12. Forecasting with Machine Learning Models 13. Other Books You May Enjoy

The attributes of the ts class

The ts class is R's built-in format for a regular univariate time series object. Before we dive into the attributes of this class, let's pause and define regular time series data and its main characteristics.

At regular time series is defined as an ordered sequence of observations over time, which is captured at equally spaced time intervals (that is, every day, week, month, and so on). Whenever this condition ceases to exist, the series becomes an irregular time series. Since this book's main topic is time series analysis and the forecasting of regular time series data, the term time series, or series, refers to regular time series data unless stated otherwise.

The main characteristics of regular time series data is as follows:

  • Cycle/period: A regular and repeating unit of time that split the series into consecutive and equally long...
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