Forecasting And Analytics With The Augmented Dynamic Adaptive Model Adam

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Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM)

Author : Ivan Svetunkov
Publisher : CRC Press
ISBN 13 : 1000992780
Total Pages : 579 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM) by : Ivan Svetunkov

Download or read book Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM) written by Ivan Svetunkov and published by CRC Press. This book was released on 2023-11-08 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting and Analytics with the Augmented Dynamic Adaptive Model (ADAM) focuses on a time series model in Single Source of Error state space form, called “ADAM” (Augmented Dynamic Adaptive Model). The book demonstrates a holistic view to forecasting and time series analysis using dynamic models, explaining how a variety of instruments can be used to solve real life problems. At the moment, there is no other tool in R or Python that would be able to model both intermittent and regular demand, would support both ETS and ARIMA, work with explanatory variables, be able to deal with multiple seasonalities (e.g. for hourly demand data) and have a support for automatic selection of orders, components and variables and provide tools for diagnostics and further improvement of the estimated model. ADAM can do all of that in one and the same framework. Given the rising interest in forecasting, ADAM, being able to do all those things, is a useful tool for data scientists, business analysts and machine learning experts who work with time series, as well as any researchers working in the area of dynamic models. Key Features: • It covers basics of forecasting, • It discusses ETS and ARIMA models, • It has chapters on extensions of ETS and ARIMA, including how to use explanatory variables and how to capture multiple frequencies, • It discusses intermittent demand and scale models for ETS, ARIMA and regression, • It covers diagnostics tools for ADAM and how to produce forecasts with it, • It does all of that with examples in R.

Bayesian Forecasting and Dynamic Models

Author : Mike West
Publisher : Springer Science & Business Media
ISBN 13 : 1475793650
Total Pages : 720 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Bayesian Forecasting and Dynamic Models by : Mike West

Download or read book Bayesian Forecasting and Dynamic Models written by Mike West and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book we are concerned with Bayesian learning and forecast ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel opment has involved thorough investigation of mathematical and sta tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.

Time Series Analysis

Author : George E. P. Box
Publisher : John Wiley & Sons
ISBN 13 : 1118674928
Total Pages : 712 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Time Series Analysis by : George E. P. Box

Download or read book Time Series Analysis written by George E. P. Box and published by John Wiley & Sons. This book was released on 2015-05-29 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Fourth Edition "The book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to model building, estimation, forecasting and control." —Mathematical Reviews Bridging classical models and modern topics, the Fifth Edition of Time Series Analysis: Forecasting and Control maintains a balanced presentation of the tools for modeling and analyzing time series. Also describing the latest developments that have occurred in the field over the past decade through applications from areas such as business, finance, and engineering, the Fifth Edition continues to serve as one of the most influential and prominent works on the subject. Time Series Analysis: Forecasting and Control, Fifth Edition provides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic models for time series and describes their use in five important areas of application: forecasting; determining the transfer function of a system; modeling the effects of intervention events; developing multivariate dynamic models; and designing simple control schemes. Along with these classical uses, the new edition covers modern topics with new features that include: A redesigned chapter on multivariate time series analysis with an expanded treatment of Vector Autoregressive, or VAR models, along with a discussion of the analytical tools needed for modeling vector time series An expanded chapter on special topics covering unit root testing, time-varying volatility models such as ARCH and GARCH, nonlinear time series models, and long memory models Numerous examples drawn from finance, economics, engineering, and other related fields The use of the publicly available R software for graphical illustrations and numerical calculations along with scripts that demonstrate the use of R for model building and forecasting Updates to literature references throughout and new end-of-chapter exercises Streamlined chapter introductions and revisions that update and enhance the exposition Time Series Analysis: Forecasting and Control, Fifth Edition is a valuable real-world reference for researchers and practitioners in time series analysis, econometrics, finance, and related fields. The book is also an excellent textbook for beginning graduate-level courses in advanced statistics, mathematics, economics, finance, engineering, and physics.

Practical Time Series Forecasting with R

Author : Galit Shmueli
Publisher : Axelrod Schnall Publishers
ISBN 13 :
Total Pages : 250 pages
Book Rating : 4./5 ( download)

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Book Synopsis Practical Time Series Forecasting with R by : Galit Shmueli

Download or read book Practical Time Series Forecasting with R written by Galit Shmueli and published by Axelrod Schnall Publishers. This book was released on 2024-02-24 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Time Series Analysis and Forecasting by Example

Author : Søren Bisgaard
Publisher : John Wiley & Sons
ISBN 13 : 1118056957
Total Pages : 346 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Time Series Analysis and Forecasting by Example by : Søren Bisgaard

Download or read book Time Series Analysis and Forecasting by Example written by Søren Bisgaard and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in detail and explain the relevant theory while also focusing on the interpretation of results in data analysis. Following a discussion of why autocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including: Graphical tools in time series analysis Procedures for developing stationary, non-stationary, and seasonal models How to choose the best time series model Constant term and cancellation of terms in ARIMA models Forecasting using transfer function-noise models The final chapter is dedicated to key topics such as spurious relationships, autocorrelation in regression, and multiple time series. Throughout the book, real-world examples illustrate step-by-step procedures and instructions using statistical software packages such as SAS, JMP, Minitab, SCA, and R. A related Web site features PowerPoint slides to accompany each chapter as well as the book's data sets. With its extensive use of graphics and examples to explain key concepts, Time Series Analysis and Forecasting by Example is an excellent book for courses on time series analysis at the upper-undergraduate and graduate levels. it also serves as a valuable resource for practitioners and researchers who carry out data and time series analysis in the fields of engineering, business, and economics.

Practical Time Series Forecasting with R

Author : Galit Shmueli
Publisher : Axelrod Schnall Publishers
ISBN 13 : 0997847956
Total Pages : 250 pages
Book Rating : 4.9/5 (978 download)

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Book Synopsis Practical Time Series Forecasting with R by : Galit Shmueli

Download or read book Practical Time Series Forecasting with R written by Galit Shmueli and published by Axelrod Schnall Publishers. This book was released on with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Galit Shmueli
Publisher : Axelrod Schnall Publishers
ISBN 13 : 0997847921
Total Pages : 232 pages
Book Rating : 4.9/5 (978 download)

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Book Synopsis Practical Time Series Forecasting with R by : Galit Shmueli

Download or read book Practical Time Series Forecasting with R written by Galit Shmueli and published by Axelrod Schnall Publishers. This book was released on 2016-08-30 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Hands-On Time Series Analysis with R

Author : Rami Krispin
Publisher : Packt Publishing Ltd
ISBN 13 : 1788624041
Total Pages : 438 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Hands-On Time Series Analysis with R by : Rami Krispin

Download or read book Hands-On Time Series Analysis with R written by Rami Krispin and published by Packt Publishing Ltd. This book was released on 2019-05-31 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build efficient forecasting models using traditional time series models and machine learning algorithms. Key FeaturesPerform time series analysis and forecasting using R packages such as Forecast and h2oDevelop models and find patterns to create visualizations using the TSstudio and plotly packagesMaster statistics and implement time-series methods using examples mentionedBook 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 foundations 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 and extract meaningful information from it using both descriptive statistics and rich data visualization tools in R such as the TSstudio, plotly, and ggplot2 packages. The later section of the book 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 cover 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 the skills needed to explore your data, identify patterns, and build a forecasting model using various traditional and machine learning methods. What you will learnVisualize time series data and derive better insightsExplore auto-correlation and master statistical techniquesUse time series analysis tools from the stats, TSstudio, and forecast packagesExplore and identify seasonal and correlation patternsWork with different time series formats in RExplore time series models such as ARIMA, Holt-Winters, and moreEvaluate high-performance forecasting solutionsWho this book is for Hands-On Time Series Analysis with R is ideal for data analysts, data scientists, and all R developers who are looking to perform time series analysis to predict outcomes effectively. A basic knowledge of statistics is required; some knowledge in R is expected, but not mandatory.

Time-Series Forecasting

Author : Chris Chatfield
Publisher : CRC Press
ISBN 13 : 1420036203
Total Pages : 281 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Time-Series Forecasting by : Chris Chatfield

Download or read book Time-Series Forecasting written by Chris Chatfield and published by CRC Press. This book was released on 2000-10-25 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space

Forecasting with Dynamic Regression Models

Author : Alan Pankratz
Publisher : John Wiley & Sons
ISBN 13 : 1118150783
Total Pages : 410 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Forecasting with Dynamic Regression Models by : Alan Pankratz

Download or read book Forecasting with Dynamic Regression Models written by Alan Pankratz and published by John Wiley & Sons. This book was released on 2012-01-20 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

Forecasting with Exponential Smoothing

Author : Rob Hyndman
Publisher : Springer Science & Business Media
ISBN 13 : 3540719180
Total Pages : 362 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Forecasting with Exponential Smoothing by : Rob Hyndman

Download or read book Forecasting with Exponential Smoothing written by Rob Hyndman and published by Springer Science & Business Media. This book was released on 2008-06-19 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4.

Forecasting with Univariate Box-Jenkins Models

Author : Alan Pankratz
Publisher : Wiley-Interscience
ISBN 13 : 9780471202387
Total Pages : 448 pages
Book Rating : 4.2/5 (23 download)

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Book Synopsis Forecasting with Univariate Box-Jenkins Models by : Alan Pankratz

Download or read book Forecasting with Univariate Box-Jenkins Models written by Alan Pankratz and published by Wiley-Interscience. This book was released on 2016-07-08 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. To update popular, unique title 2. To continue the strong sales pattern of the First Edition in a market devoid of head-on competition 3. To increase the pedagogical effectiveness of the book (now with a textbook writer/co-author) 4. To penetrate the industrial sector more

Time Series Analysis: Forecasting & Control, 3/E

Author :
Publisher : Pearson Education India
ISBN 13 : 9788131716335
Total Pages : 620 pages
Book Rating : 4.7/5 (163 download)

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Book Synopsis Time Series Analysis: Forecasting & Control, 3/E by :

Download or read book Time Series Analysis: Forecasting & Control, 3/E written by and published by Pearson Education India. This book was released on 1994-09 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a complete revision of a classic, seminal, and authoritative text that has been the model for most books on the topic written since 1970. It explores the building of stochastic (statistical) models for time series and their use in important areas of application -forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.

The Handbook of Forecasting

Author : Spyros G. Makridakis
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 632 pages
Book Rating : 4.:/5 (43 download)

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Book Synopsis The Handbook of Forecasting by : Spyros G. Makridakis

Download or read book The Handbook of Forecasting written by Spyros G. Makridakis and published by John Wiley & Sons. This book was released on 1982 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Intermittent Demand Forecasting

Author : John E. Boylan
Publisher : John Wiley & Sons
ISBN 13 : 1119135303
Total Pages : 403 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Intermittent Demand Forecasting by : John E. Boylan

Download or read book Intermittent Demand Forecasting written by John E. Boylan and published by John Wiley & Sons. This book was released on 2021-06-02 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute.

Forecasting and Time Series Analysis

Author : Douglas C. Montgomery
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 408 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Forecasting and Time Series Analysis by : Douglas C. Montgomery

Download or read book Forecasting and Time Series Analysis written by Douglas C. Montgomery and published by McGraw-Hill Companies. This book was released on 1990 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical, user-oriented second edition describes how to use statistical modeling and analysis methods for forecasting and prediction problems. Statistical and mathematical terms are introduced only as they are needed, and every effort has been made to keep the mathematical and statistical prerequisites to a minimum. Every technique that is introduced is illustrated by fully worked numerical examples. Not only is the coverage of traditional forecasting methods greatly expanded in this new edition, but a number of new techniques and methods are covered as well.

Forecasting Economic Time Series

Author : Michael Clements
Publisher : Cambridge University Press
ISBN 13 : 9780521634809
Total Pages : 402 pages
Book Rating : 4.6/5 (348 download)

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Book Synopsis Forecasting Economic Time Series by : Michael Clements

Download or read book Forecasting Economic Time Series written by Michael Clements and published by Cambridge University Press. This book was released on 1998-10-08 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.