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Time series modelling and smoothing methods for sample surveys / David A. Binder.: CS11-613/88-22E-PDF

"Classical seasonal ARIMA models and their state-space representation are reviewed. The modified Kalman filter and modified fixed point smoothing algorithms using partially improper prior distributions are shown. The adaptation of these techniques to data which are subject to correlated survey error is given. We discuss likelihood maximization, smoothing methods and confidence interval estimation. Some of the algorithms needed to perform the computations are described"--Abstract.

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.837175&sl=0

Publication information
Department/Agency
  • Canada. Statistics Canada. Methodology Branch.
TitleTime series modelling and smoothing methods for sample surveys / David A. Binder.
Series title
  • Working paper ; 88-22
Publication typeMonograph - View Master Record
Language[English]
FormatDigital text
Electronic document
Note(s)
  • "Working paper no. SSMD-88-022 E."
  • Digitized edition from print [produced by Statistics Canada].
  • Includes bibliographic references.
  • Prefatory material in English and French.
Publishing information
  • [Ottawa] : Statistics Canada, 1988.
Author / Contributor
  • Binder, David A. (David Anthony),1949-
Description43 p.
Catalogue number
  • CS11-613/88-22E-PDF
Departmental catalogue number11-613E
Subject terms
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