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A Generalized Dynamic Stochastic Model for the Interpolation, Extrapolation and Benchmarking of Time Series

Pierre-Arthur Cholette

出版	Methodology Branch, Business Survey Methods Division, Statistics Canada, 1997
URL	http://books.google.com.hk/books?id=W8MyswEACAAJ&hl=&source=gbs_api

註釋

Time series data are often subject to statistical adjustments needed to increase accuracy, replace missing values and/or facilitate data analysis. Common adjustments made to original observations are signal extraction (e.g. seasonal adjustment), benchmarking, interpolation and extrapolation. In this document, we present a general dynamic stochastic regression model, from which all these adjustments can be performed simultaneously. Futhermore, we extend current methods to include those cases where the signal follows a mixed model (deterministics and stochastic components) and the errors are autocorrelated and hetoroscedastic.