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Seasonal Adjustment with the X-11 Method: Lecture Notes in Statistics, cartea 158

Autor Dominique Ladiray, Benoit Quenneville
en Limba Engleză Paperback – 10 ian 2001
The authors, Dominique Ladiray and Benoit Quenneville, provide a unique and comprehensive r~view of the X-11 Method of seasonal adjustment. They review the original X-11 Method developed at the US Bureau of the Census in the mid-1960's, the X-ll core of the X-ll-ARTMA Method developed at Statistics Canada in the 1970's, and the X-11 module in the X- 12-ARTMA Method developed more recently at the Bureau of the Census. The review will prove extremely useful to anyone working in the field of seasonal adjustment who wants to understand the X-11 Method and how it fits into the broader picture of seasonal adjustment. What the authors designate as the X-11 Method was originally desig­ nated the X-11 Variant of the Census Method IT Seasonal Adjustment Program. It was the culmination of the pioneering work undertaken at the Bureau of the Census by Julius Shiskin in the 1950's. Shiskin introduced the Census Method T Seasonal Adjustment Program in 1954 and soon followed it with the introduction of Method TT in 1957.
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Specificații

ISBN-13: 9780387951713
ISBN-10: 0387951717
Pagini: 256
Ilustrații: XXII, 256 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.36 kg
Ediția:Softcover reprint of the original 1st ed. 2001
Editura: Springer
Colecția Springer
Seria Lecture Notes in Statistics

Locul publicării:New York, NY, United States

Public țintă

Professional/practitioner

Cuprins

1 Brief History of Seasonal Adjustment.- 2 Outline of the X-11 Method.- 2.1 Components and Decomposition Models.- 2.2 Moving Averages.- 2.3 A Simple Seasonal Adjustment Algorithm.- 2.4 The Basic Algorithm of the X-11 Method.- 2.5 Extreme Observations and Calendar Effects.- 2.6 The Iterative Principle of X-11.- 2.7 From Census X-11 to X-11-ARIMA and X-12-ARIMA.- 3 Moving Averages.- 3.1 Some Definitions and a Little Theory.- 3.2 The Symmetric Moving Averages Used in X-11.- 3.3 Musgrave Asymmetric Moving Averages.- 3.4 The X-11 Moving Average Filter.- 4 The Various Tables.- 4.1 B: Preliminary Estimation of Extreme Values and Calendar Effects.- 4.2 C: Final Estimation of Extreme Values and Calendar Effects.- 4.3 D: Final Estimation of the Different Componentst.- 4.4 E: Components Modified for Large Extreme Values.- 4.5 F: Seasonal Adjustment Quality Measures.- 5 Modelling of the Easter Effect.- 5.1 The Easter Holiday.- 5.2 The X-11-ARIMA Models.- 5.3 The X-12-ARIMA Models.- References.

Caracteristici

Includes supplementary material: sn.pub/extras