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Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series (Lecture Notes in Statistics) download epub

by Pierre A. Cholette,Estela Bee Dagum


Epub Book: 1489 kb. | Fb2 Book: 1629 kb.

A unified view of signal extraction, benchmarking, interpolation and extrapolation of time series. Time series data are often subject to statistical adjustments needed to increase accuracy, replace missing values and/or facilitate data analysis. The most common adjustments made to original observations are signal extraction (. smoothing), benchmarking, interpolation and extrapolation.

Estela Bee Dagum is Professor at the Faculty of Statistical Science of the . Series: Lecture Notes in Statistics (Book 186).

Dr. Dagum is the author of the X11-ARIMA seasonal adjustment method widely applied by statistical agencies and central banks.

Some of the most common adjustments are benchmarking, interpolation, temporal distribution, calendarization, and reconciliation. This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models.

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The Components of Time Series. The Cholette-Dagum Regression-Based Benchmarking Method - The Additive Model. Covariance Matrices for Benchmarking and Reconciliation Methods. The Cholette-Dagum Regression-Based Benchmarking Method - The Multiplicative Model. The Denton Method and its Variants. Temporal Distribution, Interpolation and Extrapolation. oceedings{gTD, title {Benchmarking, temporal distribution, and reconciliation methods for time series}, author {Estela Bee Dagum and Pierre A. Cholette}, year {2006} }. Estela Bee Dagum, Pierre A.

Estela Bee Dagum, Pierre A. They are used by decision makers to plan for a better future, by governments to promote prosperity, by central banks to control inflation, by unions to bargain for higher wages, by hospital, school boards, manufacturers, builders, transportation companies, and by consumers in general. Some of the most common adjustments are benchmarking, interpolation, temporal distribution, calendarization, and reconciliation.

Benchmarking, temporal distribution, and reconciliation methods for time series, Estela Bee Dagum, Pierre A. New York : Springer, c2006. SERIES: Lecture notes in statistics ; 88. CALL NUMBER: QA 276. PUBLISHER: New York : Springer, 2006. SERIES: Lecture notes in statistics ; 186. Call number: Ha 3.

Dagum, Estela Be. holette, Pierre . enchmarking, Temporal Distribution, And Reconciliation Methods For Time Series. New York : Springer, 2006. These citations may not conform precisely to your selected citation style. Please use this display as a guideline and modify as needed.

Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series Dagum Estela Bee, Cholette Pierre A. Springer 9780387311029 : In modern economies, time series play a crucial r.

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Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series Time Series: Theory and Methods . Report "Benchmarking, temporal distribution, and reconciliation methods for time series (LNS0186, Springer 2006)".

Time series play a crucial role in modern economies at all levels of activity and are used by decision makers to plan for a better future. Before publication time series are subject to statistical adjustments and this is the first statistical book to systematically deal with the methods most often applied for such adjustments. Regression-based models are emphasized because of their clarity, ease of application, and superior results. Each topic is illustrated with real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed a real data example is followed throughout the book.


Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series (Lecture Notes in Statistics) download epub
Mathematics
Author: Pierre A. Cholette,Estela Bee Dagum
ISBN: 0387311025
Category: Science & Math
Subcategory: Mathematics
Language: English
Publisher: Springer; 2006 edition (May 10, 2006)
Pages: 410 pages