MSSA vs. Multivariate Regularized Expectation Maximization for Data Cleaning
22 Pages Posted: 20 Jul 2016
Date Written: July 19, 2016
Abstract
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.
Keywords: Data Cleaning, SSA, MSSA, M-REM, Multivariate Regularized Expectation Maximization
JEL Classification: C1, C14, C22, C63, E44, F65, G1, Y1
Suggested Citation: Suggested Citation
Dash, Jan and Zhang, Yan, MSSA vs. Multivariate Regularized Expectation Maximization for Data Cleaning (July 19, 2016). Available at SSRN: https://ssrn.com/abstract=2811717 or http://dx.doi.org/10.2139/ssrn.2811717
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