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: Abdol S. Soofi; Liangyue Cao Название: Modelling and Forecasting Financial Data ISBN: 1461353106 ISBN-13(EAN): 9781461353102 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic.
Автор: Yuriy Kharin Название: Robustness in Statistical Forecasting ISBN: 3319008390 ISBN-13(EAN): 9783319008394 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines robustness of time series forecasting. It evaluates sensitivity of the forecast risks to distortions and presents new robust forecasting procedures.
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 book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.
Автор: E. Tabeau; Anneke van den Berg Jeths; Christopher Название: Forecasting Mortality in Developed Countries ISBN: 9048156602 ISBN-13(EAN): 9789048156603 Издательство: Springer Рейтинг: Цена: 29768.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Information on future mortality trends is essential for population forecasts, public health policy, actuarial studies, and many other purposes.
Автор: Helmut L?tkepohl Название: Forecasting Aggregated Vector ARMA Processes ISBN: 3540172084 ISBN-13(EAN): 9783540172086 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This study is concerned with forecasting time series variables and the impact of the level of aggregation on the efficiency of the forecasts. The present study contains major extensions of that research and also summarizes the earlier results to the extent they are of interest in the context of this study.
Автор: Lean Yu; Shouyang Wang; Kin Keung Lai Название: Foreign-Exchange-Rate Forecasting with Artificial Neural Networks ISBN: 1441944044 ISBN-13(EAN): 9781441944047 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting.
Автор: Ajoy K. Palit; Dobrivoje Popovic Название: Computational Intelligence in Time Series Forecasting ISBN: 1849969701 ISBN-13(EAN): 9781849969703 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.
Автор: Bernd M?ller; Uwe Reuter Название: Uncertainty Forecasting in Engineering ISBN: 3642072054 ISBN-13(EAN): 9783642072055 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Observations of uncertainty in measured data with time improves forecasting capability in a wide range of fields in engineering. Coverage places emphasis on forecasting based on fuzzy random processes as well as forecasting involving fuzzy neuronal networks.
Автор: Peter Hingley; Marc Nicolas Название: Forecasting Innovations ISBN: 3642071538 ISBN-13(EAN): 9783642071539 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a practical guide to solutions for forecasting demand for services and products in international markets - and much more than just a listing of dry theoretical methods. Leading experts present studies on improving methods for forecasting numbers of incoming patent filings at the European Patent Office.
Автор: Alexander B?nner Название: Forecasting Models for the German Office Market ISBN: 3834915254 ISBN-13(EAN): 9783834915252 Издательство: Springer Рейтинг: Цена: 10760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This work is motivated by the research gap evident in the area of forecasting models for the German office market. Since rent, price or yield forecasting research is mainly done by commercially oriented organizations, this work delivers an examination from a scientific point of view. Thus the focus is set on an empirical investigation of several rent and total yield forecasting models for nine major German cities. Their applicability and performance are analyzed and city as well as forecasting horiz- specific patterns are determined and interpreted. After the literature review, mainly covering Anglo-Saxon research, I derive the theoretical foundations which are important in executing the empirical part of the work. Therefore, I discuss theoretically general real estate market characteristics, the specifics of time series and panel data, common forecasting models, and forecasting techniques as well as performance measures. The major findings of the first part of the empirical work, which contains the rent series investigation, is that ARIMA, GARCH and multivariate regression models are generally able to forecast rent series in the German office market. Furthermore, I observed that GARCH models are able to outperform single ARIMA models for forecasting horizons of three to five years, when increased volatility appears within the respective city rent series. Moreover, univariate models outperform multivariate regression models in the short run. On the other hand, multivariate regression models outperform the univariate models in the longer run. However, I found cities where one model permanently dominates.
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