Title of article
Regularized Autoregressive Multiple Frequency Estimation
Author/Authors
Bei, Chen University of Waterloo - Department of Statistics and Actuarial Science, Canada , Yulia, R. Gel University of Waterloo - Department of Statistics and Actuarial Science, Canada
From page
141
To page
166
Abstract
The paper addresses a problem of tracking multiple number of frequencies using Regularized Autoregressive (RAR) approximation. The RAR procedure allows to decrease approximation bias, comparing to other AR-based frequency detection methods, while still providing competitive variance of sample estimates. We show that the RAR estimates of multiple periodicities are consistent in probability and illustrate dynamics of RAR in respect to sample size and signal-to-noise ration by simulations
Keywords
Autoregressive approximation , frequency tracking , least squares method , periodic time series , regularization
Journal title
Journal of the Iranian Statistical Society (JIRSS)
Journal title
Journal of the Iranian Statistical Society (JIRSS)
Record number
2578548
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