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Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R

By : Rami Krispin
3.8 (11)
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Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R

3.8 (11)
By: Rami Krispin

Overview of this book

Time-series analysis is the art of extracting meaningful insights from, and revealing patterns in, time-series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series. This book explores the basics of time-series analysis with R and lays the foundation you need to build forecasting models. You will learn how to preprocess raw time-series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data using both descriptive statistics and rich data visualization tools in R including the TSstudio, plotly, and ggplot2 packages. The book then delves into traditional forecasting models such as time-series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also work on advanced time-series regression models with machine learning algorithms such as random forest and Gradient Boosting Machine using the h2o package. By the end of this book, you will have developed the skills necessary for exploring your data, identifying patterns, and building a forecasting model using various traditional and machine learning methods.
Table of Contents (14 chapters)
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Working with zoo and xts Objects

In the previous chapter, we introduced the core class in R for time series data, the ts object. In this chapter, we will focus on another common data structure for time series data—the zoo class and its extension and the xts class, from the zoo and xts packages respectively. Those two classes are popular in the domain of financial time series analysis (that is, stock prices, indices, and so on), mainly due to their index format, which can store external date and time objects such as the Date, POSIXct/lt, yearmon, and yearqtr classes. Throughout this chapter, we will introduce methods and techniques for creating, manipulating, and visualizing zoo and xts objects.

In this chapter, we will cover the following topics:

  • Creating, working with, and manipulating zoo and xts objects
  • The attributes of the zoo and xts classes
  • The yearmon and yearqtr...
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