Download or read book An Improved State Space Representation for Cyclical Time Series written by John Haywood and published by . This book was released on 1999 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 2001 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Applications of Computer Aided Time Series Modeling written by Masanao Aoki and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of three parts: Part One is composed of two introductory chapters. The first chapter provides an instrumental varible interpretation of the state space time series algorithm originally proposed by Aoki (1983), and gives an introductory account for incorporating exogenous signals in state space models. The second chapter, by Havenner, gives practical guidance in apply ing this algorithm by one of the most experienced practitioners of the method. Havenner begins by summarizing six reasons state space methods are advanta geous, and then walks the reader through construction and evaluation of a state space model for four monthly macroeconomic series: industrial production in dex, consumer price index, six month commercial paper rate, and money stock (Ml). To single out one of the several important insights in modeling that he shares with the reader, he discusses in Section 2ii the effects of sampling er rors and model misspecification on successful modeling efforts. He argues that model misspecification is an important amplifier of the effects of sampling error that may cause symplectic matrices to have complex unit roots, a theoretical impossibility. Correct model specifications increase efficiency of estimators and often eliminate this finite sample problem. This is an important insight into the positive realness of covariance matrices; positivity has been emphasized by system engineers to the exclusion of other methods of reducing sampling error and alleviating what is simply a finite sample problem. The second and third parts collect papers that describe specific applications.
Download or read book Below the Line written by Robert Stephens and published by . This book was released on 2000 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time Series Modelling with Unobserved Components written by Matteo M. Pelagatti and published by CRC Press. This book was released on 2015-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the unobserved components model (UCM) having many advantages over more popular forecasting techniques based on regression analysis, exponential smoothing, and ARIMA, the UCM is not well known among practitioners outside the academic community. Time Series Modelling with Unobserved Components rectifies this deficiency by giving a practical o
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
Download or read book On Log transformations Vector Autoregressions and Empirical Evidence written by John Haywood and published by . This book was released on 2000 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book SAS for Forecasting Time Series Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
Download or read book The Structural Econometric Time Series Analysis Approach written by Arnold Zellner and published by Cambridge University Press. This book was released on 2004-10-21 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing together a collection of previously published work, this book provides a discussion of major considerations relating to the construction of econometric models that work well to explain economic phenomena, predict future outcomes and be useful for policy-making. Analytical relations between dynamic econometric structural models and empirical time series MVARMA, VAR, transfer function, and univariate ARIMA models are established with important application for model-checking and model construction. The theory and applications of these procedures to a variety of econometric modeling and forecasting problems as well as Bayesian and non-Bayesian testing, shrinkage estimation and forecasting procedures are also presented and applied. Finally, attention is focused on the effects of disaggregation on forecasting precision and the Marshallian Macroeconomic Model that features demand, supply and entry equations for major sectors of economies is analysed and described. This volume will prove invaluable to professionals, academics and students alike.
Download or read book Filtering None Linear State Space Models Methods and Economic Applications written by Kai Ming Lee and published by Rozenberg Publishers. This book was released on 2010 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling of Transport Demand written by V.A Profillidis and published by Elsevier. This book was released on 2018-10-23 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers assess the validity and accuracy of demand forecasts. Forecasting and evaluating transport demand is an essential task of transport professionals and researchers that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand forecasts are necessary for companies and government entities when planning future fleet size, human resource needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport Demand help readers solve the problems they face on a daily basis. Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most suitable solution for all types of transport applications. - Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand - Provides a theoretical analysis and formulations that are clearly presented for ease of understanding - Covers analysis for all modes of transportation - Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results
Download or read book Bayesian Hierarchical Models written by Peter D. Congdon and published by CRC Press. This book was released on 2019-09-16 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website
Download or read book Advances in Remote Sensing for Global Forest Monitoring written by Erkki Tomppo and published by MDPI. This book was released on 2021-09-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.
Download or read book IJCNN 93 Nagoya written by and published by . This book was released on 1993 with total page 1034 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Tourism Management written by Arch G. Woodside and published by CABI. This book was released on 2008 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides in-depth empirical reports on specific topics within five general areas of tourism management and marketing: (1) scanning and sense making; (2) planning; (3) implementing; (4) evaluating actions/process and performance outcomes; and (5) administering. Offering descriptions, tools and examples of tourism management decision making, the book is useful for students in tourism and management and for tourism executives. It has 27 chapters and a subject index.
Download or read book SAS for Forecasting Time Series written by John C. Brocklebank and published by John Wiley & Sons. This book was released on 2003-07-14 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easy-to-read and comprehensive, this book shows how the SAS System performs multivariate time series analysis and features the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. The interrelationship of SAS/ETS procedures is demonstrated with an accompanying discussion of how the choice of a procedure depends on the data to be analysed and the reults desired. Other topics covered include detecting sinusoidal components in time series models and performing bivariate corr-spectral analysis and comparing the results with the standard transfer function methodology. The authors? unique approach to integrating students in a variety of disciplines and industries. Emphasis is on correct interpretation of output to draw meaningful conclusions. The volume, co-pubished by SAS and JWS, features both theory and practicality, and accompanies a soon-to-be extensive library of SAS hands-on manuals in a multitude of statistical areas. The book can be used with a number of hardware-specific computing machines including CMS, Mac, MVS, Opem VMS Alpha, Opmen VMS VAX, OS/390, OS/2, UNIX, and Windows.
