MSSA vs. Multivariate Regularized Expectation Maximization for Data Cleaning

Previously we introduced Singular Spectrum Analysis SSA and its multivariate extension MSSA as a powerful tool for cleaning data. Here we compare MSSA with the data filling algorithm M-REM (Multivariate Regularized Expectation Maximization). We compare theoretical methodology, numerical stability, algorithm capability, flexibility and speed. Theory and numerical tests indicate that MSSA is superior to M-REM for data cleaning

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Year of publication:	2016
Authors:	Dash, Jan
Other Persons:	Zhang, Yan (contributor)
Publisher:	[2016]: [S.l.] : SSRN
Subject:	Theorie \| Theory \| Multivariate Analyse \| Multivariate analysis \| Erwartungsbildung \| Expectation formation

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