Modeling and Forecasting Electricity Demand, Kevin Berk
Автор: Harvey, Andrew C. Название: Forecasting, structural time series models and the kalman filter ISBN: 0521405734 ISBN-13(EAN): 9780521405737 Издательство: Cambridge Academ Рейтинг: Цена: 6018.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose. It is unique in its use of Kalman filtering with econometric and time series modelling.
Автор: Byrne Название: Structural Equation Modeling With AMOS ISBN: 1138797030 ISBN-13(EAN): 9781138797031 Издательство: Taylor&Francis Рейтинг: Цена: 8879.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos.
Автор: Hyndman Название: Forecasting with Exponential Smoothing ISBN: 3540719164 ISBN-13(EAN): 9783540719168 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems.
Автор: Alho Название: Statistical Demography and Forecasting ISBN: 0387225382 ISBN-13(EAN): 9780387225388 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Sustainability of pension systems, intergeneration fiscal equity under population aging, and accounting for health care benefits for future retirees are examples of problems that cannot be solved without understanding the nature of population forecasts and their uncertainty. Similarly, the accuracy of population estimates directly affects both the distributions of formula-based government allocations to sub-national units and the apportionment of political representation. The book develops the statistical foundation for addressing such issues. Areas covered include classical mathematical demography, event history methods, multi-state methods, stochastic population forecasting, sampling and census coverage, and decision theory. The methods are illustrated with empirical applications from Europe and the U.S.For statisticians the book provides a unique introduction to demographic problems in a familiar language. For demographers, actuaries, epidemiologists, and professionals in related fields, the book presents a unified statistical outlook on both classical methods of demography and recent developments. To facilitate its classroom use, exercises are included. Over half of the book is readily accessible to undergraduates, but more maturity may be required to benefit fully from the complete text. Knowledge of differential and integral calculus, matrix algebra, basic probability theory, and regression analysis is assumed.
Автор: Douglas C. Montgomery,Cheryl L. Jennings,Murat Kul Название: Introduction to Time Series Analysis and Forecasting ISBN: 1118745116 ISBN-13(EAN): 9781118745113 Издательство: Wiley Рейтинг: Цена: 18208.00 р. Наличие на складе: Поставка под заказ.
Описание: Praise for the First Edition " [t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics.
Описание: This is a revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970. It focuses on practical techniques throughout, rather than a rigorous mathematical treatment of the subject. It explores the building of stochastic (statistical) models for time series and their use in important areas of application forecasting, model specification, estimation, modeling the effects of intervention events, and process control, among others. In addition to meticulous modifications in content and improvements in style, the new edition incorporates several new topics in an effort to modernize the subject matter. These topics include extensive discussions of multivariate time series, smoothing, likelihood function based on the state space model, autoregressive models, structural component models and deterministic seasonal components, and nonlinear and long memory models.
Автор: Jan G. De Gooijer Название: Elements of Nonlinear Time Series Analysis and Forecasting ISBN: 3319432516 ISBN-13(EAN): 9783319432519 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107069394 ISBN-13(EAN): 9781107069398 Издательство: Cambridge Academ Рейтинг: Цена: 19325.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Описание: This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose. It is unique in its use of Kalman filtering with econometric and time series modelling.
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