Practical Time Series Forecasting With R
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Practical Time Series Forecasting With R
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Author : Galit Shmueli
language : en
Publisher: Axelrod Schnall Publishers
Release Date : 2024-02-24
Practical Time Series Forecasting With R written by Galit Shmueli and has been published by Axelrod Schnall Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-24 with Business & Economics categories.
Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time series data. This edition features the R fable package, full color, enhanced organization, and new material. It includes: Popular forecasting methods including smoothing algorithms, regression models, ARIMA, neural networks, deep learning, and ensembles - A practical approach to evaluating the performance of forecasting solutions - A business-analytics exposition focused on linking time-series forecasting to business goals - Guided cases for integrating the acquired knowledge using real data - End-of-chapter problems to facilitate active learning - Data, R code, and instructor materials on companion website - Affordable and globally-available textbook, available in hardcover, paperback, and Kindle formats Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, information systems, finance, and management.
Practical Time Series Forecasting With R
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Author : Galit Shmueli
language : en
Publisher: Axelrod Schnall Publishers
Release Date : 2016-07-23
Practical Time Series Forecasting With R written by Galit Shmueli and has been published by Axelrod Schnall Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-23 with Mathematics categories.
Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time-series data. Featuring improved organization and new material, the Second Edition also includes: - Popular forecasting methods including smoothing algorithms, regression models, and neural networks - A practical approach to evaluating the performance of forecasting solutions - A business-analytics exposition focused on linking time-series forecasting to business goals - Guided cases for integrating the acquired knowledge using real data - End-of-chapter problems to facilitate active learning - A companion site with data sets, R code, learning resources, and instructor materials (solutions to exercises, case studies) - Globally-available textbook, available in both softcover and Kindle formats Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management. For more information, visit forecastingbook.com
Practical Time Series Forecasting With R
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Author : Galit Shmueli
language : en
Publisher:
Release Date : 2015-07-17
Practical Time Series Forecasting With R written by Galit Shmueli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-17 with Forecasting categories.
"Practical time series forecasting with R is a hands-on introduction to quantitative forecasting of time series. Quantitative forecasting is an important component of decision making in a wide range of areas and across many business functions including economic forecasting, workload projections, sales forecasts, and transportation demand ... The book introduces readers to the most popular statistical models and data mining algorithms used in practice. It covers issues relating to different steps of the forecasting process, form goal definion through data collection, visualization, pre-processing, modeling, performance evaluation to implementation and communication."--Back cover.
Automated Time Series Forecasting Made Easy With R
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Author : Nigel D. Lewis
language : en
Publisher:
Release Date : 2017-07-13
Automated Time Series Forecasting Made Easy With R written by Nigel D. Lewis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-13 with Data mining categories.
Finally, A Blueprint for Automated Time Series Forecasting with R! Automated Time Series Forecasting Made Easy with R offers a practical tutorial that uses hands-on examples to step through real-world applications using clear and practical case studies. Through this process it takes you on a gentle, fun and unhurried journey to creating your own models to forecast time series data. Whether you are new to time series forecasting or a veteran, this book offers a powerful set of tools for quickly and easily gaining insight from your data using R. NO EXPERIENCE REQUIRED: Through a simple to follow step by step process you will learn how to build time series forecasting models using R. Once you have mastered the process, it will be easy for you to translate your knowledge into your own powerful applications. YOUR PERSONAL BLUE PRINT: Through a simple to follow intuitive step by step process, you will learn how to use the most popular time series forecasting models using R. Once you have mastered the process, it will be easy for you to translate your knowledge to assess your own data. THIS BOOK IS FOR YOU IF YOU WANT: Focus on explanations rather than mathematical derivation Practical illustrations that use real data. Illustrations to deepen your understanding. Worked examples in R you can easily follow and immediately implement. Ideas you can actually use and try on your own data. TAKE THE SHORTCUT: This guide was written for people who want to get up to speed as quickly as possible. YOU'LL LEARN HOW TO: Unleash the power the Prophet forecasting algorithm. Master the award winning Theta method. Use the component form exponential smoothing framework. Design successful applications using classical ARIMA modeling. Adapt the flexible BATS and TBATS framework for optimum success. Deploy the multiple aggregation prediction algorithm. Explore the potential of simple moving averages. For each time series forecasting technique, every step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks. Using plain language, this book offers a simple, intuitive, practical, non-mathematical, easy to follow guide to the most successful ideas, outstanding techniques and usable solutions available using R. Everything you need to get started is contained within this book. Automated Time Series Forecasting Made Easy with R is your very own hands on practical, tactical, easy to follow guide to mastery. Buy this book today and accelerate your progress!
Time Series Forecasting With R
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Author : Alex Peak
language : en
Publisher: Independently Published
Release Date : 2025-11-20
Time Series Forecasting With R written by Alex Peak and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-20 with Computers categories.
TIME SERIES FORECASTING WITH R: PRACTICAL TECHNIQUES AND PREDICTIVE MODELS FOR DATA-DRIVEN INSIGHTS Unlock the power of your data and transform it into actionable insights with Time Series Forecasting with R-a comprehensive, hands-on guide designed for beginners, experienced analysts, and data-driven professionals alike. Whether you're predicting sales trends, stock prices, energy demand, or customer behavior, this book equips you with the tools and techniques to forecast confidently and accurately. This book provides clear, step-by-step guidance that eliminates the guesswork. Instead of relying solely on complex formulas or intimidating statistical theory, you'll learn to work directly with your data in R using practical, reproducible methods. Each technique is explained with clarity, accompanied by real-world examples, ready-to-use R code, and insights drawn from modern forecasting best practices. Inside, you'll discover: Foundations of Time Series: Understand the core principles of time series data, including trends, seasonality, and cyclical behavior. Learn how to structure and preprocess your data for optimal forecasting results. Exploratory Data Analysis: Visualize and dissect your series to uncover hidden patterns, anomalies, and correlations that form the backbone of reliable predictions. Statistical and Advanced Models: Apply ARIMA, ETS, state-space models, and more to capture both simple and complex temporal dynamics. Machine Learning Approaches: Harness the power of random forests, gradient boosting, and neural networks to detect non-linear patterns and interactions, while ensuring reproducibility in R. Feature Engineering and Automation: Learn how to transform raw data into meaningful predictors and automate forecasting pipelines for multiple datasets, saving time and improving efficiency. Real-World Applications: Work with practical examples from retail, finance, energy, and environmental datasets, demonstrating how forecasting informs business decisions and operational strategies. Visualization and Reporting: Communicate your forecasts effectively using clear plots, interactive dashboards, and automated reports, ensuring that your insights are actionable and easily interpreted by stakeholders. Best Practices and Future Trends: Explore hybrid modeling, ensemble methods, AI integration, real-time forecasting, and emerging trends that will keep your skills at the forefront of data science. With Time Series Forecasting with R, you don't just learn to generate numbers-you gain the confidence to turn those numbers into meaningful insights, predictions, and strategies. The book is packed with examples, practical exercises, and expert guidance, making it suitable for analysts, data scientists, business professionals, and students eager to apply forecasting to real-world challenges. Take control of your data, make informed decisions, and forecast the future with precision. This book is your ultimate companion to mastering time series forecasting in R.
Practical Time Series Analysis
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Author : Dr. Avishek Pal
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-28
Practical Time Series Analysis written by Dr. Avishek Pal and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-28 with Computers categories.
Step by Step guide filled with real world practical examples. About This Book Get your first experience with data analysis with one of the most powerful types of analysis—time-series. Find patterns in your data and predict the future pattern based on historical data. Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide Who This Book Is For This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods. What You Will Learn Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project Develop an understanding of loading, exploring, and visualizing time-series data Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series Take advantage of exponential smoothing to tackle noise in time series data Learn how to use auto-regressive models to make predictions using time-series data Build predictive models on time series using techniques based on auto-regressive moving averages Discover recent advancements in deep learning to build accurate forecasting models for time series Gain familiarity with the basics of Python as a powerful yet simple to write programming language In Detail Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. Style and approach This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.
Practical Time Series Analysis
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Author : Aileen Nielsen
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-09-20
Practical Time Series Analysis written by Aileen Nielsen and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
International Journal Of Forecasting
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Author : International institute of forecasters
language : en
Publisher:
Release Date : 1993
International Journal Of Forecasting written by International institute of forecasters and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
Practical Time Series Forecasting
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Author : Galit Shmueli
language : en
Publisher:
Release Date : 2016-07-11
Practical Time Series Forecasting written by Galit Shmueli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-11 with categories.
PRACTICAL TIME SERIES FORECASTING is a hands-on introduction to quantitative forecasting of time series. Quantitative forecasting, known as forecasting analytics, is an important component of decision making in a wide range of areas and across many business functions including economic forecasting, workload projections, sales forecasts, and transportation demand. Forecasting is also widely used in automated applications such as forecasting flight delays, web keyword search volume, and weather. Forecasting is heavily used in many areas outside of business, such as in demography and climatology. This book introduces readers to the most popular statistical models and data mining algorithms used in practice. It covers issues relating to different steps of the forecasting process, from goal definition through data collection, visualization, pre-processing, modeling, performance evaluation to implementation and communication. The third edition offers improved organization, updated software screenshots, and additional material.PRACTICAL TIME SERIES FORECASTING is suitable for courses on forecasting at the upper-undergraduate and graduate levels, and in professional business analytics and data science programs. It offers clear explanations, examples, end-of-chapter problems and cases. Methods are illustrated using XLMiner®, an Excel® add-on. However, any software that has time series forecasting capabilities can be used with the book. For R users, an R edition of this textbook is also available.
International Journal Of Forecasting
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Author :
language : en
Publisher:
Release Date : 1995
International Journal Of Forecasting written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Business forecasting categories.