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Activity Number: 450
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract - #306332
Title: Coupling X-12-Arima-Seats with a Multidimensional Direct Filter Approach for Signal Extraction in Nonstationary Seasonal Time Series
Author(s): Chris Blakely*+
Companies: U.S. Department of Commerce
Address: 2647 Connecticut Ave. NW, Washington, DC, 20008, United States
Keywords: Signal Extraction ; X-12-ARIMA-SEATS ; Direct Filter Approach ; Seasonal Adjustment

This paper introduces a coupling strategy of model-based signal extraction with a newly developed iterative approach to multidimensional direct concurrent filtering (M-DFA). The process of extracting desired signals in nonstationary seasonal time series is fortified using a three-step approach to obtain better control over user-defined properties. These properties can include timeliness of turning-points in trend and/or cycles, signal-noise ratio characteristics, and quality of seasonal adjustment. Futhermore, we show how the uSim software developed by the author simplifies this hybrid approach of user-defined signal extraction using a simple combination of graphical-user-interface controls for adjusting regARIMA model fitting, X-12-ARIMA-SEATS signal decompostions, and timeliness/accuracy controls in an iterative M-DFA algorithm. Finally, we give numerous numerical examples to demonstrate the potential and robustness of the proposed hybrid method.

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