Multirate systems and filter banks
Multirate systems and filter banks
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Improved frequency selective filters
Computational Statistics & Data Analysis - Special issue: Computational econometrics
Toeplitz And Circulant Matrices: A Review (Foundations and Trends(R) in Communications and Information Theory)
Preface: Special Issue on Nonlinear Modelling and Financial Econometrics
Computational Statistics & Data Analysis
Editorial: 2nd Special Issue on Statistical Signal Extraction and Filtering
Computational Statistics & Data Analysis
Signal extraction and filtering by linear semiparametric methods
Computational Statistics & Data Analysis
Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter
Computational Statistics & Data Analysis
Linear dynamic harmonic regression
Computational Statistics & Data Analysis
Removing seasonality under a changing regime: Filtering new car sales
Computational Statistics & Data Analysis
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The Wiener-Kolmogorov signal extraction filters, which are widely used in econometric analysis, are constructed on the basis of statistical models of the processes generating the data. The models can be heuristic devices that may be specified in whichever ways are appropriate to ensure that the filters have the desired characteristics. The digital Butterworth filters, which are described and illustrated in the paper, are specified in this way. The components of an econometric time series often give rise to spectral structures that fall within well-defined frequency bands that are isolated from each other by spectral dead spaces. For such cases, a Fourier-based method is proposed, which operates in the frequency domain. This new method can be assimilated to a finite-sample Wiener-Kolmogorov framework.