On a family of finite moving‐average trend filters for the ends of series

Alistair G. Gray

37 citations0/0 files storedJournal of Forecasting

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Forecasting Techniques and Applications Time Series Analysis and Forecasting Statistical and numerical algorithms

Abstract

Abstract A family of finite end filters is constructed using a minimum revisions criterion and based on a local dynamic model operating within the span of a given finite central filter. These end filters are equivalent to evaluating the central filter with unavailable future observations replaced by constrained optimal linear predictions. Two prediction methods are considered: best linear unbiased prediction and best linear biased prediction where the bias is time invariant. The properties of these end filters are determined. In particular, they are compared to X‐11 end filters and to the case where the central filter is evaluated with unavailable future observations predicted by global ARIMA models as in X‐11‐ARIMA or X‐12‐ARIMA. Copyright © 2002 John Wiley & Sons, Ltd.

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1978Seasonal Analysis of Economic Time Series 2002Issues Involved With the Seasonal Adjustment of Economic Time Series 1990Forecasting, structural time series models and the Kalman filter 1982Local Trend Estimation and Seasonal Adjustment of Economic and Social Time Series 1983The Prediction of Time Series With Trends and Seasonalities 1998Analysis of Patent Data—A Mixed-Poisson-Regression-Model Approach 1984Issues Involved with the Seasonal Adjustment of Economic Time Series 1980Data revisions with moving average seasonal adjustment procedures

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