A generalized dynamic stochastic model for the interpolation, extrapolation and benchmarking of time series / by Pierre A. Cholette, Estela Bee Dagum and Zhao-Guo Chen. : CS11-617/97-3E-PDF

"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. Furthermore, we extend current methods to include those cases where the signal follows a mixed model (deterministic and stochastic components) and the errors are autocorrelated and heteroscedastic"--Abstract.

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