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Hands-On Time Series Analysis with R
Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R: Perform time series analysis and forecasting using R

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Key benefits

  • Perform time-series analysis and forecasting using R packages such as forecast and h2o
  • Develop models and find patterns to create visualizations using the TSstudio and plotly packages
  • Learn statistics and implement time-series methods with the help of examples

Description

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.

Who is this book for?

Hands-On Time Series Analysis with R is ideal for data analysts, data scientists, and R developers looking to perform time-series analysis to predict outcomes effectively. Basic knowledge of statistics is required to understand the concepts covered in this book. Also, some experience in R will be helpful.

What you will learn

  • Visualize time-series data and derive useful insights
  • Study auto-correlation and understand statistical techniques
  • Use time-series analysis tools from the stats, TSstudio, and forecast packages
  • Explore and identify seasonal and correlation patterns
  • Work with different time-series formats in R
  • Discover time-series models such as ARIMA, Holt-Winters, and more
  • Evaluate high-performance forecasting solutions

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 31, 2019
Length: 448 pages
Edition : 1st
Language : English
ISBN-13 : 9781788624046
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Languages :
Concepts :

What do you get with eBook?

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Product Details

Publication date : May 31, 2019
Length: 448 pages
Edition : 1st
Language : English
ISBN-13 : 9781788624046
Category :
Languages :
Concepts :

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Frequently bought together


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Total $ 125.97
Hands-On Time Series Analysis with R
$38.99
R Statistics Cookbook
$26.99
Machine Learning with R
$59.99
Total $ 125.97 Stars icon
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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8
(11 Ratings)
5 star 54.5%
4 star 9.1%
3 star 18.2%
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1 star 18.2%
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Blaise F Egan Apr 02, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Practical, hands-on guide to forecasting using R. Easy to use, as all the Packt books are.
Amazon Verified review Amazon
Raquel Dourado Sep 13, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is very didactic and it has valuable explanations.Organized and elegant.A must-read!
Amazon Verified review Amazon
Abhinivesh Devathi Jul 30, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book has been a boon for my work, as I've never been able to understand all the weird quirks in R with time series data. Since I just started working at a financial institution after graduating, time series analysis is really important.The author took the approach of starting with the basics and building your understanding step-by-step. It was really easy to follow and each step was shown visually. Additionally, the author included their code so that you can take their examples and use it for your own application.Finally, the author created his own package for Time Series analysis, TSstudio, which worked great and allowed for interactive plots through plotly.Will definitely keep this book on my desk!
Amazon Verified review Amazon
Naftali Jun 20, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I enjoyed reading the book and learned a lot. Very practical with down-to-earth examples.
Amazon Verified review Amazon
Suarez Mar 01, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have been through the book, despite some challenges with code, it was a great experience learning it and useful for my work. Great.
Amazon Verified review Amazon
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