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Forecasting Innovations, Peter Hingley; Marc Nicolas


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Цена: 19564.00р.
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Автор: Peter Hingley; Marc Nicolas
Название:  Forecasting Innovations
ISBN: 9783642071539
Издательство: Springer
Классификация:



ISBN-10: 3642071538
Обложка/Формат: Paperback
Страницы: 268
Вес: 0.39 кг.
Дата издания: 14.10.2010
Язык: English
Размер: 234 x 156 x 15
Основная тема: Economics
Подзаголовок: Methods for Predicting Numbers of Patent Filings
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


Robustness in Statistical Forecasting

Автор: Yuriy Kharin
Название: Robustness in Statistical Forecasting
ISBN: 3319345680 ISBN-13(EAN): 9783319345680
Издательство: Springer
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Цена: 14673.00 р.
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Описание: This book examines robustness of time series forecasting. It evaluates sensitivity of the forecast risks to distortions and presents new robust forecasting procedures.

Innovations in Macroeconomics

Автор: Paul J.J. Welfens
Название: Innovations in Macroeconomics
ISBN: 3642442056 ISBN-13(EAN): 9783642442056
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Modern macroeconomics suffers from an unclear link between short-term Keynesian analysis and long-term growth modelling. With respect to economic policy - in particular innovation policy - the analysis implies major changes, concerning both EU countries and other leading OECD economies.

Statistical Demography and Forecasting

Автор: Alho
Название: Statistical Demography and Forecasting
ISBN: 0387225382 ISBN-13(EAN): 9780387225388
Издательство: Springer
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Цена: 21661.00 р.
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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.

Lead Markets in Age-Based Innovations

Автор: Nils Levsen
Название: Lead Markets in Age-Based Innovations
ISBN: 3658088141 ISBN-13(EAN): 9783658088149
Издательство: Springer
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Цена: 9141.00 р.
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Описание: Nils Levsen focuses on the international diffusion of product and service innovations for elderly users. Lead markets are characterized by their early adoption of innovations and their influence on design choice in a subsequent international diffusion process.

Forecasting, structural time series models and the kalman filter

Автор: Harvey, Andrew C.
Название: Forecasting, structural time series models and the kalman filter
ISBN: 0521405734 ISBN-13(EAN): 9780521405737
Издательство: Cambridge Academ
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Цена: 6018.00 р.
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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.

Time Series Models for Business and Economic Forecasting

Автор: Franses
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521520916 ISBN-13(EAN): 9780521520911
Издательство: Cambridge Academ
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Цена: 7445.00 р.
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Описание: With a new author team contributing decades of practical experience, this fully updated second edition textbook summarises the most critical decisions, techniques and steps in creating effective forecasting models. Includes all new theoretical and practical exercises geared at guiding students through the steps of creating forecasting models on their own.

Introduction to Time Series Analysis and Forecasting

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
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Цена: 18208.00 р.
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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.

Time Series Analysis: Forecasting and Control, 4th Edition

Автор: Box G. E. P.
Название: Time Series Analysis: Forecasting and Control, 4th Edition
ISBN: 0470272848 ISBN-13(EAN): 9780470272848
Издательство: Wiley
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Цена: 18533.00 р.
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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.

Elements of Nonlinear Time Series Analysis and Forecasting

Автор: Jan G. De Gooijer
Название: Elements of Nonlinear Time Series Analysis and Forecasting
ISBN: 3319432516 ISBN-13(EAN): 9783319432519
Издательство: Springer
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Цена: 18167.00 р.
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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.

Forecasting High-Frequency Volatility Shocks

Автор: Holger K?mm
Название: Forecasting High-Frequency Volatility Shocks
ISBN: 3658125950 ISBN-13(EAN): 9783658125950
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This thesis presents a new strategy that unites qualitative and quantitative mass data in form of text news and tick-by-tick asset prices to forecast the risk of upcoming volatility shocks.

Economic and Business Forecasting

Автор: Silvia John
Название: Economic and Business Forecasting
ISBN: 1118497090 ISBN-13(EAN): 9781118497098
Издательство: Wiley
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Цена: 9108.00 р.
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Описание: Equipping analysts, practitioners, and graduate students with a statistical framework to make effective decisions based on the application of simple economic and statistical methods, this title offers a comprehensive and practical approach to quantifying and accurate forecasting of key variables.

Forecasting International Migration in Europe: A Bayesian View

Автор: Jakub Bijak; Arkadiusz Wisniowski
Название: Forecasting International Migration in Europe: A Bayesian View
ISBN: 940073395X ISBN-13(EAN): 9789400733954
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This book examines how to forecast the international migration component in a way that can be used for population forecasts using the probabilistic approach. It applies Bayesian statistical methods to an under-researched area of population forecasting.


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