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Probability Forecasting

Probability Forecasting
Author: Lawrence Ambrose Hughes
Publisher:
Total Pages: 96
Release: 1980
Genre: Precipitation forecasting
ISBN:

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Probabilistic Forecasting and Bayesian Data Assimilation

Probabilistic Forecasting and Bayesian Data Assimilation
Author: Sebastian Reich
Publisher: Cambridge University Press
Total Pages: 308
Release: 2015-05-14
Genre: Computers
ISBN: 1316299422

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In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.


Probabilistic Forecasting and Bayesian Data Assimilation

Probabilistic Forecasting and Bayesian Data Assimilation
Author: Sebastian Reich
Publisher: Cambridge University Press
Total Pages: 308
Release: 2015-05-14
Genre: Computers
ISBN: 1107069394

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This book covers key ideas and concepts. It is an ideal introduction for graduate students in any field where Bayesian data assimilation is applied.


Forecasting with Univariate Box - Jenkins Models

Forecasting with Univariate Box - Jenkins Models
Author: Alan Pankratz
Publisher: John Wiley & Sons, Incorporated
Total Pages: 584
Release: 1983-08-30
Genre: Mathematics
ISBN:

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Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.


Handbook of Economic Forecasting

Handbook of Economic Forecasting
Author: Graham Elliott
Publisher: Elsevier
Total Pages: 667
Release: 2013-08-23
Genre: Business & Economics
ISBN: 0444627405

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The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics


Seasonal Climate: Forecasting and Managing Risk

Seasonal Climate: Forecasting and Managing Risk
Author: Alberto Troccoli
Publisher: Springer Science & Business Media
Total Pages: 462
Release: 2008-02-22
Genre: Science
ISBN: 1402069901

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Originally formed around a set of lectures presented at a NATO Advanced Study Institute (ASI), this book has grown to become organised and presented rather more as a textbook than as a standard "collection of proceedings". This therefore is the first unified reference ‘textbook’ in seasonal to interannual climate predictions and their practical uses. Written by some of the world’s leading experts, the book covers a rapidly-developing science of prime social concern.


A Companion to Economic Forecasting

A Companion to Economic Forecasting
Author: Michael P. Clements
Publisher: John Wiley & Sons
Total Pages: 616
Release: 2008-04-15
Genre: Social Science
ISBN: 140517191X

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A Companion to Economic Forecasting provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.


Wind Power Ensemble Forecasting

Wind Power Ensemble Forecasting
Author: André Gensler
Publisher: kassel university press GmbH
Total Pages: 216
Release: 2019-01-16
Genre: Weights and measures
ISBN: 3737606366

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This thesis describes performance measures and ensemble architectures for deterministic and probabilistic forecasts using the application example of wind power forecasting and proposes a novel scheme for the situation-dependent aggregation of forecasting models. For performance measures, error scores for deterministic as well as probabilistic forecasts are compared, and their characteristics are shown in detail. For the evaluation of deterministic forecasts, a categorization by basic error measure and normalization technique is introduced that simplifies the process of choosing an appropriate error measure for certain forecasting tasks. Furthermore, a scheme for the common evaluation of different forms of probabilistic forecasts is proposed. Based on the analysis of the error scores, a novel hierarchical aggregation technique for both deterministic and probabilistic forecasting models is proposed that dynamically weights individual forecasts using multiple weighting factors such as weather situation and lead time dependent weighting. In the experimental evaluation it is shown that the forecasting quality of the proposed technique is able to outperform other state of the art forecasting models and ensembles.


Statistical Methods for Forecasting

Statistical Methods for Forecasting
Author: Bovas Abraham
Publisher: John Wiley & Sons
Total Pages: 474
Release: 2009-09-25
Genre: Mathematics
ISBN: 0470317299

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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.