Forecasting: Principles and Practice (2024)

Table of Contents
Hot Books New Books Great book about forecasting with relevant examples。 The book provides underlying concepts of forecasting， such as moving-avg， exponential， ARISMA， and etc。 Also this book touches the advanced concepts of forecasting， such as Neutral Network， and Autocorrelated Regression。 Readers with prior knowledge about Statistics and Math are suitable for reading this book。 ჩემთვის მარტივად გასაგებად და დაღეჭილად წერია，იმაზე უხარისხოდ გავარჩიე ვიდრე ვისურვებდი A free online textbook with running code （in R）。 Very easy to read。 Time series made accessible。 This what textbooks should be like。 This was a great reference， but after working with it for a while I realized the newer version has moved into the tidyverse！ Do yourself a favor and go there first Easy to read and implement， this well-figured book is a good intro to time series and forecasting。 This is a great quick introduction to modern forecasting。 The chapters are short and instructive。 The drawback is in how high-level the explanations of forecasting models is。 It offers a good conceptual explanation of many topics， but lacks the derivations of results and even comprehensive coverage of how modeling methods like autocorrelation and moving averages work。 Great book to supplement with a more technical forecasting text。 This is a fantastic book introducing time series forecasting covering a wide range of topics （including dynamic regression and ARIMA）。 Time series forecasting has stumped me for a long time especially trying to integrate machine learning elements into it。 However this book has opened the doors into the possibilities to forecast with only a couple lines of code using the tsibble package。 As forecasting and more importantly， accurate forecasting is crucial for businesses to succeed in this competi This is a fantastic book introducing time series forecasting covering a wide range of topics （including dynamic regression and ARIMA）。 Time series forecasting has stumped me for a long time especially trying to integrate machine learning elements into it。 However this book has opened the doors into the possibilities to forecast with only a couple lines of code using the tsibble package。 As forecasting and more importantly， accurate forecasting is crucial for businesses to succeed in this competitive environment， time series forecasting beyond what's done in Excel is critical。Recommendation thanks: An individual on my slack channel who went to the 2020 Rstudio conference recommended this book as the best workshop in the whole conference。 Suggestions: Yes but only if you plan on starting to complete time series forecasting by coding。 I plan on re-reading this book in the future。Resource: https://otexts。com/fpp3/ 。。。more Always good to refresh on this book every few years。 Excellent applied guide to forecasting。 One of the most practical textbooks I've ever read。 Combining the explanations with the code in one book is extremely helpful。 Excellent applied guide to forecasting。 One of the most practical textbooks I've ever read。 Combining the explanations with the code in one book is extremely helpful。 。。。more Read the 2nd edition。Very practical materials。 Covered almost everything except state space models。 Eminently practical overview of statistical forecasting methods with accompanying R code。 Includes a survey of qualitative techniques as well as sufficient technical documentation of quantitative methods without getting bogged down in proofs & derivations。Excellent resource & reference。To complete the irresistible value proposition， it's available as a free online ebook via otexts: https://www。otexts。org/fpp Eminently practical overview of statistical forecasting methods with accompanying R code。 Includes a survey of qualitative techniques as well as sufficient technical documentation of quantitative methods without getting bogged down in proofs & derivations。Excellent resource & reference。To complete the irresistible value proposition， it's available as a free online ebook via otexts: https://www。otexts。org/fpp 。。。more Fantastic reference for anyone doing time series analysis。 Perhaps the de-facto standard among free and public domain textbooks for this area of study/work。 Forecasting: Principles and Practice by Hyndman and Athanasopoulos is a great intro for time series analysis。 The book covers a wide variety of topics （including dynamic regression and ARIMA） and focuses on the core principles behind these techniques。 It is able to avoid the pitfall of being a sole formula collection while it delivers the most important model equations。 The language is comprehensible but formal。 The great thing about this textbook is its user orientation。 Every procedure is acco Forecasting: Principles and Practice by Hyndman and Athanasopoulos is a great intro for time series analysis。 The book covers a wide variety of topics （including dynamic regression and ARIMA） and focuses on the core principles behind these techniques。 It is able to avoid the pitfall of being a sole formula collection while it delivers the most important model equations。 The language is comprehensible but formal。 The great thing about this textbook is its user orientation。 Every procedure is accompanied by a full R-script so you can immediately use it for your own research and tackle more complex models。Some topics would have deserved a more detailed explanation （e。g。 exponential smoothing and dynamic regression）。 If you are completely new to time series analysis you might need some additional online resources to understand these topics。Oh and don't forget: It's free！ 。。。more

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Forecasting: Principles and Practice (1)

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  • Create Date：2021-07-20 07:51:49
  • Update Date：2024-06-10
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  • Author：Rob J. Hyndman
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Forecasting is required in many situations。 Deciding whether to build another power generation plant in the next five years requires forecasts of future demand。 Scheduling staff in a call centre next week requires forecasts of call volumes。 Stocking an inventory requires forecasts of stock requirements。 Telecommunication routing requires traffic forecasts a few minutes ahead。 Whatever the circ*mstances or time horizons involved， forecasting is an important aid in effective and efficient planning。 This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly。 Examples use R with many data sets taken from the authors' own consulting experience。 In this third edition， all chapters have been updated to cover the latest research and forecasting methods。 One new chapter has been added on time series features。 The latest version of the book is freely available online at http: //OTexts。com/fpp3。

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Pawin ，

Great book about forecasting with relevant examples。 The book provides underlying concepts of forecasting， such as moving-avg， exponential， ARISMA， and etc。 Also this book touches the advanced concepts of forecasting， such as Neutral Network， and Autocorrelated Regression。 Readers with prior knowledge about Statistics and Math are suitable for reading this book。

Bubu ，

ჩემთვის მარტივად გასაგებად და დაღეჭილად წერია，იმაზე უხარისხოდ გავარჩიე ვიდრე ვისურვებდი

Adrian ，

A free online textbook with running code （in R）。 Very easy to read。 Time series made accessible。 This what textbooks should be like。

Leah ，

This was a great reference， but after working with it for a while I realized the newer version has moved into the tidyverse！ Do yourself a favor and go there first

Corey Runkel ，

Easy to read and implement， this well-figured book is a good intro to time series and forecasting。

Duncan McKinnon ，

This is a great quick introduction to modern forecasting。 The chapters are short and instructive。 The drawback is in how high-level the explanations of forecasting models is。 It offers a good conceptual explanation of many topics， but lacks the derivations of results and even comprehensive coverage of how modeling methods like autocorrelation and moving averages work。 Great book to supplement with a more technical forecasting text。

Stephen Lung ，

This is a fantastic book introducing time series forecasting covering a wide range of topics （including dynamic regression and ARIMA）。 Time series forecasting has stumped me for a long time especially trying to integrate machine learning elements into it。 However this book has opened the doors into the possibilities to forecast with only a couple lines of code using the tsibble package。 As forecasting and more importantly， accurate forecasting is crucial for businesses to succeed in this competi This is a fantastic book introducing time series forecasting covering a wide range of topics （including dynamic regression and ARIMA）。 Time series forecasting has stumped me for a long time especially trying to integrate machine learning elements into it。 However this book has opened the doors into the possibilities to forecast with only a couple lines of code using the tsibble package。 As forecasting and more importantly， accurate forecasting is crucial for businesses to succeed in this competitive environment， time series forecasting beyond what's done in Excel is critical。Recommendation thanks: An individual on my slack channel who went to the 2020 Rstudio conference recommended this book as the best workshop in the whole conference。 Suggestions: Yes but only if you plan on starting to complete time series forecasting by coding。 I plan on re-reading this book in the future。Resource: https://otexts。com/fpp3/ 。。。more

Frank ，

Always good to refresh on this book every few years。

Nate ，

Excellent applied guide to forecasting。 One of the most practical textbooks I've ever read。 Combining the explanations with the code in one book is extremely helpful。 Excellent applied guide to forecasting。 One of the most practical textbooks I've ever read。 Combining the explanations with the code in one book is extremely helpful。 。。。more

Bing Wang ，

Read the 2nd edition。Very practical materials。 Covered almost everything except state space models。

Daniel ，

Eminently practical overview of statistical forecasting methods with accompanying R code。 Includes a survey of qualitative techniques as well as sufficient technical documentation of quantitative methods without getting bogged down in proofs & derivations。Excellent resource & reference。To complete the irresistible value proposition， it's available as a free online ebook via otexts: https://www。otexts。org/fpp Eminently practical overview of statistical forecasting methods with accompanying R code。 Includes a survey of qualitative techniques as well as sufficient technical documentation of quantitative methods without getting bogged down in proofs & derivations。Excellent resource & reference。To complete the irresistible value proposition， it's available as a free online ebook via otexts: https://www。otexts。org/fpp 。。。more

Rajesh ，

Fantastic reference for anyone doing time series analysis。 Perhaps the de-facto standard among free and public domain textbooks for this area of study/work。

Joshua Hruzik ，

Forecasting: Principles and Practice by Hyndman and Athanasopoulos is a great intro for time series analysis。 The book covers a wide variety of topics （including dynamic regression and ARIMA） and focuses on the core principles behind these techniques。 It is able to avoid the pitfall of being a sole formula collection while it delivers the most important model equations。 The language is comprehensible but formal。 The great thing about this textbook is its user orientation。 Every procedure is acco Forecasting: Principles and Practice by Hyndman and Athanasopoulos is a great intro for time series analysis。 The book covers a wide variety of topics （including dynamic regression and ARIMA） and focuses on the core principles behind these techniques。 It is able to avoid the pitfall of being a sole formula collection while it delivers the most important model equations。 The language is comprehensible but formal。 The great thing about this textbook is its user orientation。 Every procedure is accompanied by a full R-script so you can immediately use it for your own research and tackle more complex models。Some topics would have deserved a more detailed explanation （e。g。 exponential smoothing and dynamic regression）。 If you are completely new to time series analysis you might need some additional online resources to understand these topics。Oh and don't forget: It's free！ 。。。more

Forecasting: Principles and Practice (2024)
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