Compositional trend filtering
نویسندگان
چکیده
Trend filtering is known as the technique for detecting piecewise linear trends in univariate time series. This extended to setting of compositional data, which are multivariate data where only relative information importance. According this, we formulate problem and present a procedure how efficiently solve it. To show usefulness this method, consider number COVID-19 infections several European countries chosen period.
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Yu-Xiang Wang1,2 [email protected] James Sharpnack3 [email protected] Alexander J. Smola1,4 [email protected] Ryan J. Tibshirani1,2 [email protected] 1 Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213 2 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213 3 Mathematics Department, University of California at San Diego, La Jolla, CA 10280 ...
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This report has been submitted forr publication outside of ITC and will probably be copyrighted if accepted for publication. It has been issued as a Technical Report forr early dissemination of its contents. In view of the transfert of copy right too the outside publisher, its distribution outside of ITC priorr to publication should be limited to peer communications and specificc requests. Afte...
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ژورنال
عنوان ژورنال: Az Eszterházy Károly Tanárképz? F?iskola tudományos közleményei
سال: 2021
ISSN: ['1216-6014', '1787-6117', '1787-5021', '1589-6498']
DOI: https://doi.org/10.33039/ami.2021.02.004