Statistical Methods for Forecasting
Aus der Reihe
Wiley Series in Probability and Statistics
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Form:Einzelkauf Download
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Sprache:Englisch
121,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
25.09.2009
Verlag
WileySeitenzahl
446 (Printausgabe)
Dateigröße
15649 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9780470317297
The Wiley-Interscience Paperback Series consists of selected books
that have been made more accessible to consumers in an effort to
increase global appeal and general circulation. With these new
unabridged softcover volumes, Wiley hopes to extend the lives of
these works by making them available to future generations of
statisticians, mathematicians, and scientists.
"This book, it must be said, lives up to the words on its
advertising cover: 'Bridging the gap between introductory,
descriptive approaches and highly advanced theoretical treatises,
it provides a practical, intermediate level discussion of a variety
of forecasting tools, and explains how they relate to one another,
both in theory and practice.' It does just that!"
-Journal of the Royal Statistical Society
"A well-written work that deals with statistical methods and models
that can be used to produce short-term forecasts, this book has
wide-ranging applications. It could be used in the context of a
study of regression, forecasting, and time series analysis by PhD
students; or to support a concentration in quantitative methods for
MBA students; or as a work in applied statistics for advanced
undergraduates."
-Choice
Statistical Methods for Forecasting is a comprehensive, readable
treatment of statistical methods and models used to produce
short-term forecasts. The interconnections between the forecasting
models and methods are thoroughly explained, and the gap between
theory and practice is successfully bridged. Special topics are
discussed, such as transfer function modeling; Kalman filtering;
state space models; Bayesian forecasting; and methods for forecast
evaluation, comparison, and control. The book provides time series,
autocorrelation, and partial autocorrelation plots, as well as
examples and exercises using real data. Statistical Methods for
Forecasting serves as an outstanding textbook for advanced
undergraduate and graduate courses in statistics, business,
engineering, and the social sciences, as well as a working
reference for professionals in business, industry, and government.
that have been made more accessible to consumers in an effort to
increase global appeal and general circulation. With these new
unabridged softcover volumes, Wiley hopes to extend the lives of
these works by making them available to future generations of
statisticians, mathematicians, and scientists.
"This book, it must be said, lives up to the words on its
advertising cover: 'Bridging the gap between introductory,
descriptive approaches and highly advanced theoretical treatises,
it provides a practical, intermediate level discussion of a variety
of forecasting tools, and explains how they relate to one another,
both in theory and practice.' It does just that!"
-Journal of the Royal Statistical Society
"A well-written work that deals with statistical methods and models
that can be used to produce short-term forecasts, this book has
wide-ranging applications. It could be used in the context of a
study of regression, forecasting, and time series analysis by PhD
students; or to support a concentration in quantitative methods for
MBA students; or as a work in applied statistics for advanced
undergraduates."
-Choice
Statistical Methods for Forecasting is a comprehensive, readable
treatment of statistical methods and models used to produce
short-term forecasts. The interconnections between the forecasting
models and methods are thoroughly explained, and the gap between
theory and practice is successfully bridged. Special topics are
discussed, such as transfer function modeling; Kalman filtering;
state space models; Bayesian forecasting; and methods for forecast
evaluation, comparison, and control. The book provides time series,
autocorrelation, and partial autocorrelation plots, as well as
examples and exercises using real data. Statistical Methods for
Forecasting serves as an outstanding textbook for advanced
undergraduate and graduate courses in statistics, business,
engineering, and the social sciences, as well as a working
reference for professionals in business, industry, and government.
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