Time series modelling and smoothing methods for sample surveys: 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: What is a permanent link?
http://publications.gc.ca/pub?id=9.837175&sl=0
MARC XML Format   MARC HTML Format

Department/Agency Statistics Canada. Methodology Branch.
Title Time series modelling and smoothing methods for sample surveys
Series Title Working paper ;
Publication Type Series - View Master Record
Language [English]
Format Electronic
Electronic Document

Archived Content

Information identified as archived is provided for reference, research or recordkeeping purposes. It is not subject to the Government of Canada Web Standards and has not been altered or updated since it was archived. Please contact the authoring department to request a format other than those available.

We invite you to consult the Frequently Asked Questions page for additional information regarding the Archived Content notice.


Having trouble opening this document?

Note: The URLs contained in this/these document(s) may no longer be functional
Note "Working paper no. SSMD-88-022 E." Digitized edition from print [produced by Statistics Canada].
Date 1988.
Number of Pages 43 p.
Catalogue Number
  • CS11-613/88-22E-PDF
Departmental Catalogue Number 11-613E
Subject Terms Surveys, Methodology