Smoothing Forecasting And Prediction Of Discrete Time Series
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Smoothing Forecasting And Prediction Of Discrete Time Series
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Author : Robert Goodell Brown
language : en
Publisher: Courier Corporation
Release Date : 2004-01-01
Smoothing Forecasting And Prediction Of Discrete Time Series written by Robert Goodell Brown and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-01 with Technology & Engineering categories.
Computer application techniques are applied to routine short-term forecasting and prediction in this classic of operations research. The text begins with a consideration of data sources and sampling intervals, progressing to discussions of time series models and probability models. An extensive overview of smoothing techniques surveys the mathematical techniques for periodically raising the estimates of coefficients in forecasting problems. Sections on forecasting and error measurement and analysis are followed by an exploration of alternatives and the applications of the forecast to specific problems, and a treatment of the handling of systems design problems ranges from observed data to decision rules. 1963 ed.
Smoothing Forecasting And Prediction Of Discrete Time Series
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Author : Robert Grover Brown
language : en
Publisher:
Release Date : 1963
Smoothing Forecasting And Prediction Of Discrete Time Series written by Robert Grover Brown and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1963 with categories.
Forecasting And Time Series Analysis
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Author : Douglas C. Montgomery
language : en
Publisher: McGraw-Hill Companies
Release Date : 1990
Forecasting And Time Series Analysis written by Douglas C. Montgomery and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematics categories.
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 Discrete Time Series Data By The Exponential Smoothing Process
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Author : Harry E. Norwood
language : en
Publisher:
Release Date : 1967
Forecasting Discrete Time Series Data By The Exponential Smoothing Process written by Harry E. Norwood and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1967 with Smoothing (Statistics) categories.
Introduction To Time Series Analysis And Forecasting
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Author : Douglas C. Montgomery
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-30
Introduction To Time Series Analysis And Forecasting written by Douglas C. Montgomery and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-30 with Mathematics categories.
Praise for the First Edition "…[t]he book is great for readers who need to applythe methods and models presented but have little background inmathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time SeriesAnalysis and Forecasting, Second Edition presents theunderlying theories of time series analysis that are needed toanalyze time-oriented data and construct real-world short- tomedium-term statistical forecasts. Authored by highly-experienced academics and professionals inengineering statistics, the Second Edition featuresdiscussions on both popular and modern time series methodologies aswell as an introduction to Bayesian methods in forecasting.Introduction to Time Series Analysis and Forecasting, SecondEdition also includes: Over 300 exercises from diverse disciplines including healthcare, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®,and R that illustrate the theory and practicality of forecastingtechniques in the context of time-oriented data New material on frequency domain and spatial temporaldata analysis Expanded coverage of the variogram and spectrum withapplications as well as transfer and intervention modelfunctions A supplementary website featuring PowerPoint®slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, SecondEdition is an ideal textbook upper-undergraduate andgraduate-levels courses in forecasting and time series. The book isalso an excellent reference for practitioners and researchers whoneed to model and analyze time series data to generate forecasts.
Smooting Forecasting And Prediction Of Discrete Time Series
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Author :
language : en
Publisher:
Release Date : 1963
Smooting Forecasting And Prediction Of Discrete Time Series written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1963 with categories.
Time Series For Data Science
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Author : Wayne A. Woodward
language : en
Publisher: CRC Press
Release Date : 2022-08-01
Time Series For Data Science written by Wayne A. Woodward and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-01 with Mathematics categories.
Data Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject. This book is an accessible guide that doesn’t require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed. Features: Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing, Holt Winters, ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs, and ensemble models composed of combinations of these models. Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy. Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics, Department of Transportation and the World Bank. There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use.
The Analysis Of Time Series
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Author : Chris Chatfield
language : en
Publisher: CRC Press
Release Date : 2016-03-30
The Analysis Of Time Series written by Chris Chatfield and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-30 with Mathematics categories.
Since 1975, The Analysis of Time Series: An Introduction has introduced legions of statistics students and researchers to the theory and practice of time series analysis. With each successive edition, bestselling author Chris Chatfield has honed and refined his presentation, updated the material to reflect advances in the field, and presented interesting new data sets. The sixth edition is no exception. It provides an accessible, comprehensive introduction to the theory and practice of time series analysis. The treatment covers a wide range of topics, including ARIMA probability models, forecasting methods, spectral analysis, linear systems, state-space models, and the Kalman filter. It also addresses nonlinear, multivariate, and long-memory models. The author has carefully updated each chapter, added new discussions, incorporated new datasets, and made those datasets available for download from www.crcpress.com. A free online appendix on time series analysis using R can be accessed at http://people.bath.ac.uk/mascc/TSA.usingR.doc. Highlights of the Sixth Edition: A new section on handling real data New discussion on prediction intervals A completely revised and restructured chapter on more advanced topics, with new material on the aggregation of time series, analyzing time series in finance, and discrete-valued time series A new chapter of examples and practical advice Thorough updates and revisions throughout the text that reflect recent developments and dramatic changes in computing practices over the last few years The analysis of time series can be a difficult topic, but as this book has demonstrated for two-and-a-half decades, it does not have to be daunting. The accessibility, polished presentation, and broad coverage of The Analysis of Time Series make it simply the best introduction to the subject available.
Time Series And Forecasting
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Author : Bruce L. Bowerman
language : en
Publisher: Brooks/Cole
Release Date : 1979
Time Series And Forecasting written by Bruce L. Bowerman and has been published by Brooks/Cole this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Mathematics categories.
Forecasting and multiple regression analysis; Forecasting time series described by trend and irregular components; Forecasting seasonal time series; The box-jenkins methodology.
Forecasting With Exponential Smoothing
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Author : Rob Hyndman
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-19
Forecasting With Exponential Smoothing written by Rob Hyndman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-19 with Mathematics categories.
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.