发帖
雷达卡
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
For more information, visit forecastingbook.com
Editorial ReviewsReview
Praise for previous editions
"The book is a little gem. I found the writing in this book to be a refreshing contrast, making technical concepts understandable."
"An excellent starting point for anyone dealing with time series forecasting. One of the best intro books on time series and forecasting I have ever seen."
-- Prof. Ron Kenett
"A concise and well-written book for MBA and Executive MBA programs. The book is especially timely as more MBA programs are using R."-- Prof. Johannes Ledolter
"Galit Shmueli has provided something that you don't see very often - a book with meat that does not have pages and pages stuffed full of equations..."-- John Seymour, "John the Math Guy"
The exposition is accessible to students with a wide range of backgrounds, and balanced between enough mathematics to explain the methods but not so much that it raises barriers to understanding... first-rate textbook at a bargain price.-- Prof. Thomas Tiahrt
[url=]Read more[/url]
About the Author
GALIT SHMUELI, PhD is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. She is co-author of the best-selling textbook Data Mining for Business Analytics, among other books and numerous publications in top journals. She has designed and instructed courses on forecasting, data mining, statistics and other data analytics topics at University of Maryland's Smith School of Business, the Indian School of Business, National Tsing Hua University and online at statistics.com
For more information, visit galitshmueli.com
KENNETH C. LICHTENDAHL JR. is an Associate Professor of Business Administration at the University of Virginia's Darden School of Business. He specializes in teaching data science to MBA students with R. He was recognized by The Case Centre as its 2015 Outstanding Case Teacher for his course Data Science in Business. His research focuses broadly on making, evaluating, and combining forecasts and has been published in leading academic journals such as Management Science.
Product Details
- Series: Practical Analytics
- Paperback: 232 pages
- Publisher: Axelrod Schnall Publishers; 2 edition (July 19, 2016)
- Language: English
- ISBN-10: 0997847913
- ISBN-13: 978-0997847918
Practical Time Series Forecasting with R A Hands-On Guide (2nd Edition).pdf
(4.31 MB, 需要: 10 个论坛币)
京公网安备 11010802022788号
