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A State Space Approach To Evaluate Multi Horizon Forecasts
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Book Synopsis A State Space Approach to Evaluate Multi-Horizon Forecasts by : Thomas Goodwin
Download or read book A State Space Approach to Evaluate Multi-Horizon Forecasts written by Thomas Goodwin and published by . This book was released on 2017 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a state space modeling framework to evaluate a set of forecasts that target the same variable but are updated along the forecast horizon. The approach decomposes forecast errors into three distinct horizon-specific processes, namely, bias, rational error and implicit error, and attributes forecast revisions to corrections for these forecast errors. We derive the conditions under which forecasts that contain error that is irrelevant to the target can still present the second moment bounds of rational forecasts. By evaluating multi-horizon daily maximum temperature forecasts for Melbourne, Australia, we demonstrate how this modeling framework analyzes the dynamics of the forecast revision structure across horizons. Understanding forecast revisions is critical for weather forecast users to determine the optimal timing for their planning decision.
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances 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.
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.
Book Synopsis Nonlinear Dynamics In Physiology: A State-space Approach by : Mark J Shelhamer
Download or read book Nonlinear Dynamics In Physiology: A State-space Approach written by Mark J Shelhamer and published by World Scientific. This book was released on 2006-12-06 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a compilation of mathematical-computational tools that are used to analyze experimental data. The techniques presented are those that have been most widely and successfully applied to the analysis of physiological systems, and address issues such as randomness, determinism, dimension, and nonlinearity. In addition to bringing together the most useful methods, sufficient mathematical background is provided to enable non-specialists to understand and apply the computational techniques. Thus, the material will be useful to life-science investigators on several levels, from physiologists to bioengineer.Initial chapters present background material on dynamic systems, statistics, and linear system analysis. Each computational technique is demonstrated with examples drawn from physiology, and several chapters present case studies from oculomotor control, neuroscience, cardiology, psychology, and epidemiology. Throughout the text, historical notes give a sense of the development of the field and provide a perspective on how the techniques were developed and where they might lead. The overall approach is based largely on the analysis of trajectories in the state space, with emphasis on time-delay reconstruction of state-space trajectories. The goal of the book is to enable readers to apply these methods to their own research.
Book Synopsis Forecasting With The Theta Method by : Kostas I. Nikolopoulos
Download or read book Forecasting With The Theta Method written by Kostas I. Nikolopoulos and published by John Wiley & Sons. This book was released on 2019-03-18 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to be published on the Theta method, outlining under what conditions the method outperforms other forecasting methods This book is the first to detail the Theta method of forecasting – one of the most difficult-to-beat forecasting benchmarks, which topped the biggest forecasting competition in the world in 2000: the M3 competition. Written by two of the leading experts in the forecasting field, it illuminates the exact replication of the method and under what conditions the method outperforms other forecasting methods. Recent developments such as multivariate models are also included, as are a series of practical applications in finance, economics, and healthcare. The book also offers practical tools in MS Excel and guidance, as well as provisional access, for the use of R source code and respective packages. Forecasting with the Theta Method: Theory and Applications includes three main parts. The first part, titled Theory, Methods, Models & Applications details the new theory about the method. The second part, Applications & Performance in Forecasting Competitions, describes empirical results and simulations on the method. The last part roadmaps future research and also include contributions from another leading scholar of the method – Dr. Fotios Petropoulos. First ever book to be published on the Theta Method Explores new theory and exact conditions under which methods would outperform most forecasting benchmarks Clearly written with practical applications Employs R – open source code with all included implementations Forecasting with the Theta Method: Theory and Applications is a valuable tool for both academics and practitioners involved in forecasting and respective software development.
Book Synopsis Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track by : Yuxiao Dong
Download or read book Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track written by Yuxiao Dong and published by Springer Nature. This book was released on 2021-09-09 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.
Book Synopsis Neural Information Processing by : Tom Gedeon
Download or read book Neural Information Processing written by Tom Gedeon and published by Springer Nature. This book was released on 2019-12-10 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 11955, is organized in topical sections on semantic and graph based approaches; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.
Book Synopsis Advanced Analytics and Learning on Temporal Data by : Georgiana Ifrim
Download or read book Advanced Analytics and Learning on Temporal Data written by Georgiana Ifrim and published by Springer Nature. This book was released on 2024-01-20 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 14343 constitutes the refereed proceedings of the 8th ECML PKDD Workshop, AALTD 2023, in Turin, Italy, in September 2023. The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis.
Book Synopsis Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles by : Michael Siek
Download or read book Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles written by Michael Siek and published by CRC Press. This book was released on 2011-12-16 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled processes and relationships between the observed descriptive variables. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory. First, some fundamentals of physical oceanography, nonlinear dynamics and chaos, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.
Book Synopsis Non-parametric Estimation of Forecast Distributions in Non-linear, Non-gaussian State Space Models by : Jason Wei Jian Ng
Download or read book Non-parametric Estimation of Forecast Distributions in Non-linear, Non-gaussian State Space Models written by Jason Wei Jian Ng and published by . This book was released on 2012 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Gaussian time series variables are prevalent in the economic and finance spheres, with state space models often employed to analyze such variables and, ultimately, to produce forecasts. A review of the relevant literature reveals that existing methods are characterized by a reliance on (potentially incorrect) parametric assumptions and are often computationally expensive. The primary aim of this thesis is to develop a non-parametric approach to forecasting - within the state space framework - with computational ease an important focus. With a view to capturing all relevant information about the likely future values of the variable of interest, the approach is used to produce non-parametric estimates of the full forecast distribution over any time horizon. Simulation experiments are used to document the accuracy of the non-parametric method relative to both correctly and incorrectly specified parametric alternatives, in a variety of relevant settings. Applying a range of methods for evaluating and comparing distributional forecasts, the non-parametric method is shown to perform significantly better, overall, than misspecified parametric alternatives while remaining competitive with correctly specified parametric estimators. Focus is then given to the development of a new non-Gaussian state space model for observed realized volatility from which estimates of forecast distributions of future volatility are produced using the non-parametric method. In an empirical illustration, the non-parametric method is used to produce sequential estimates of the out-of-sample one-step-ahead forecast distribution of realized volatility on the S&P500 index during the recent financial crisis. A resampling technique for measuring sampling variation in an estimated forecast distribution is also demonstrated. The proposed filtering algorithm is further extended to cater, in particular, for multi-step-ahead forecasting and multivariate systems. A simulation-based version of the algorithm is also illustrated, with the algorithm in this form seen to be a computationally efficient alternative to existing particle filtering algorithms.
Book Synopsis Data Fusion and Data Mining for Power System Monitoring by : Arturo Román Messina
Download or read book Data Fusion and Data Mining for Power System Monitoring written by Arturo Román Messina and published by CRC Press. This book was released on 2020-06-03 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications. Features Focuses on systematic illustration of data mining and fusion in power systems Covers issues of standards used in the power industry for data mining and data analytics Applications to a wide range of power networks are provided including distribution and transmission networks Provides holistic approach to the problem of data mining and data fusion using cutting-edge methodologies and technologies Includes applications to massive spatiotemporal data from simulations and actual events
Book Synopsis Economic Forecasting by : Graham Elliott
Download or read book Economic Forecasting written by Graham Elliott and published by Princeton University Press. This book was released on 2016-04-05 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and integrated approach to economic forecasting problems Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike
Download or read book River Flow 2004 written by Massimo Greco and published by CRC Press. This book was released on 2004-06-15 with total page 1469 pages. Available in PDF, EPUB and Kindle. Book excerpt: RiverFlow 2004 is the Second International Conference on Fluvial Hydraulics, organized as speciality conferences under the auspices of the International Association of Hydraulic Engineering and Research (IAHR) within its Fluvial Hydraulics and Eco Hydraulics Sections. RiverFlow conferences are a significant forum of discussion for many researchers
Book Synopsis Routledge Library Editions: Econometrics by : Various
Download or read book Routledge Library Editions: Econometrics written by Various and published by Routledge. This book was released on 2019-01-15 with total page 5228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reissuing works originally published between 1929 and 1991, this collection of 17 volumes presents a variety of considerations on Econometrics, from introductions to specific research works on particular industries. With some volumes on models for macroeconomics and international economies, this is a widely interesting set of economic texts. Input/Output methods and databases are looked at in some volumes while others look at Bayesian techniques, linear and non-linear models. This set will be of use to those in industry and business studies, geography and sociology as well as politics and economics.
Book Synopsis Modelling Seasonality by : Svend Hylleberg
Download or read book Modelling Seasonality written by Svend Hylleberg and published by Oxford University Press, USA. This book was released on 1992 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume brings together leading papers on the existing standard economic theory of seasonality as well as papers which apply newer statistical tools to the modelling of seasonal phenomena. It includes a discussion of the X-11 method of seasonal adjustment, as well as an assessment ofrecent developments in the field.
Book Synopsis Predictions, Nonlinearities and Portfolio Choice by : Friedrich Christian Kruse
Download or read book Predictions, Nonlinearities and Portfolio Choice written by Friedrich Christian Kruse and published by BoD – Books on Demand. This book was released on 2012 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance researchers and asset management practitioners put a lot of effort into the question of optimal asset allocation. With this respect, a lot of research has been conducted on portfolio decision making as well as quantitative modeling and prediction models. This study brings together three fields of research, which are usually analyzed in an isolated manner in the literature: - Predictability of asset returns and their covariance matrix - Optimal portfolio decision making - Nonlinear modeling, performed by artificial neural networks, and their impact on predictions as well as optimal portfolio construction Including predictability in asset allocation is the focus of this work and it pays special attention to issues related to nonlinearities. The contribution of this study to the portfolio choice literature is twofold. First, motivated by the evidence of linear predictability, the impact of nonlinear predictions on portfolio performances is analyzed. Predictions are empirically performed for an investor who invests in equities (represented by the DAX index), bonds (represented by the REXP index) and a risk-free rate. Second, a solution to the dynamic programming problem for intertemporal portfolio choice is presented. The method is based on functional approximations of the investor's value function with artificial neural networks. The method is easily capable of handling multiple state variables. Hence, the effect of adding predictive parameters to the state space is the focus of analysis as well as the impacts of estimation biases and the view of a Bayesian investor on intertemporal portfolio choice. One important empirical result shows that residual correlation among state variables have an impact on intertemporal portfolio decision making.
Book Synopsis Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media by : Keikhosrokiani, Pantea
Download or read book Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media written by Keikhosrokiani, Pantea and published by IGI Global. This book was released on 2022-12-30 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence has been utilized in a diverse range of industries as more people and businesses discover its many uses and applications. A current field of study that requires more attention, as there is much opportunity for improvement, is the use of artificial intelligence within literary works and social media analysis. The Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media presents contemporary developments in the adoption of artificial intelligence in textual analysis of literary works and social media and introduces current approaches, techniques, and practices in data science that are implemented to scrap and analyze text data. This book initiates a new multidisciplinary field that is the combination of artificial intelligence, data science, social science, literature, and social media study. Covering key topics such as opinion mining, sentiment analysis, and machine learning, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
