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Time Scale Estimation by Tracking Parameter Variation
Author(s) -
Belcher John,
Tunnicliffe Wilson Granville
Publication year - 2000
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00183
Subject(s) - mathematics , autoregressive model , series (stratigraphy) , scale (ratio) , variation (astronomy) , statistics , scale parameter , sampling (signal processing) , time series , estimation , autoregressive–moving average model , econometrics , computer science , paleontology , physics , management , filter (signal processing) , quantum mechanics , astrophysics , economics , computer vision , biology
A quasi‐periodic time series is sampled at a varying but unknown rate. An autoregressive moving‐average model is fitted to the resulting discrete series and the time variation of its parameters is estimated. The functional dependence of the parameters on the sampling rate is then used to estimate this rate and to reconstruct the true time scale.

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