Full Product Details
Author: Estela Bee Dagum ,
Pierre A. Cholette
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 2006 ed.
Volume: 186
Dimensions:
Width: 15.50cm
, Height: 2.20cm
, Length: 23.50cm
Weight: 1.320kg
ISBN: 9780387311029
ISBN 10: 0387311025
Pages: 410
Publication Date: 10 May 2006
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: In Print
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Reviews
From the reviews: It is an excellent reference book for people working in this area. B. Abraham for Short Book Reviews of the ISI, December 2006 The book's intended audience is students in graduate and final-year undergraduate courses in econometrics and time series analysis, who could use it as a textbook, as well as researchers and practitioners in governments and business, who could use it as a reference book. ... This book provides a good, detailed discussion of the statistical methods used by statistical agencies for adjusting time series data from official statistics. The chapters are quite self-contained, facilitating the book's use as a reference. (Andreas Karlsson, Technometrics, Vol. 49 (4), 2007) This book is a very detailed course on statistical methods for such adjustments, focused on bench marking, interpolation, temporal distribution, calendarization, and reconciliation. ... Each chapter of the book is self-contained and illustrates the methods discussed with a large number of real data examples. The book can be recommended as a very useful textbook for students as well as a reference book for researchers and practitioners in this field. (Ryszard Doman, Zentralblatt MATH, Vol. 1107 (9), 2007) Time series play a central role in contemporary modern economics. ... the authors discuss several procedures, widely used by statistical agencies, for such adjustments as benchmarking, reconciliation or balancing, temporal distribution, interpolation and calendarization. ... The clarity of exposition and the fact that each chapter is self-contained make the book easily accessible not only for experienced readers such as academic researchers or practitioners in government and business, but also for graduate or even for last-year undergraduate students. (Dan Emanuel Popovici, Mathematical Reviews, Issue 2007 e) This monograph, the first devoted to the interrelated topics of its title, is a distillation of its authors' unrivaled research and practical experience at Statistics Canada in the topic areas. ... Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series an essential reference for statistical institutes and central banks and for statisticians and economists who have to address similar time series data issues. ... The book could serve as a textbook for a graduate-level special topics course. (Baoline Chen and David Findley, Journal of the American Statistical Association, Vol. 103 (484), December, 2008)
From the reviews: <p> It is an excellent reference book for people working in this area. B. Abraham for Short Book Reviews of the ISI, December 2006 <p> The booka (TM)s intended audience is students in graduate and final-year undergraduate courses in econometrics and time series analysis, who could use it as a textbook, as well as researchers and practitioners in governments and business, who could use it as a reference book. a ] This book provides a good, detailed discussion of the statistical methods used by statistical agencies for adjusting time series data from official statistics. The chapters are quite self-contained, facilitating the booka (TM)s use as a reference. (Andreas Karlsson, Technometrics, Vol. 49 (4), 2007) <p> This book is a very detailed course on statistical methods for such adjustments, focused on bench marking, interpolation, temporal distribution, calendarization, and reconciliation. a ] Each chapter of the book is self-contained and illustrates the methods discussed with a large number of real data examples. The book can be recommended as a very useful textbook for students as well as a reference book for researchers and practitioners in this field. (Ryszard Doman, Zentralblatt MATH, Vol. 1107 (9), 2007) <p> Time series play a central role in contemporary modern economics. a ] the authors discuss several procedures, widely used by statistical agencies, for such adjustments as benchmarking, reconciliation or balancing, temporal distribution, interpolation and calendarization. ... The clarity of exposition and the fact that each chapter is self-contained make the book easily accessible not only for experienced readers such as academic researchers orpractitioners in government and business, but also for graduate or even for last-year undergraduate students. (Dan Emanuel Popovici, Mathematical Reviews, Issue 2007 e)
From the reviews: It is an excellent reference book for people working in this area. B. Abraham for Short Book Reviews of the ISI, December 2006 The book's intended audience is students in graduate and final-year undergraduate courses in econometrics and time series analysis, who could use it as a textbook, as well as researchers and practitioners in governments and business, who could use it as a reference book. ... This book provides a good, detailed discussion of the statistical methods used by statistical agencies for adjusting time series data from official statistics. The chapters are quite self-contained, facilitating the book's use as a reference. (Andreas Karlsson, Technometrics, Vol. 49 (4), 2007) This book is a very detailed course on statistical methods for such adjustments, focused on bench marking, interpolation, temporal distribution, calendarization, and reconciliation. ... Each chapter of the book is self-contained and illustrates the methods discussed with a large number of real data examples. The book can be recommended as a very useful textbook for students as well as a reference book for researchers and practitioners in this field. (Ryszard Doman, Zentralblatt MATH, Vol. 1107 (9), 2007) Time series play a central role in contemporary modern economics. ... the authors discuss several procedures, widely used by statistical agencies, for such adjustments as benchmarking, reconciliation or balancing, temporal distribution, interpolation and calendarization. ... The clarity of exposition and the fact that each chapter is self-contained make the book easily accessible not only for experienced readers such as academic researchers or practitioners in government and business, but also for graduate or even for last-year undergraduate students. (Dan Emanuel Popovici, Mathematical Reviews, Issue 2007 e) This monograph, the first devoted to the interrelated topics of its title, is a distillation of its authors' unrivaled research and practical experience at Statistics Canada in the topic areas. ... Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series an essential reference for statistical institutes and central banks and for statisticians and economists who have to address similar time series data issues. ... The book could serve as a textbook for a graduate-level special topics course. (Baoline Chen and David Findley, Journal of the American Statistical Association, Vol. 103 (484), December, 2008)
