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.
|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|
|Electronic Document|| |
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|Note||"Working paper no. SSMD-88-022 E." Digitized edition from print [produced by Statistics Canada].|
|Number of Pages||43 p.|
|Departmental Catalogue Number||11-613E|
|Subject Terms||Surveys, Methodology|
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