Indonesian Journal of Electrical Engineering and Computer Science
Vol 12, No 6: June 2014

Impact of Missing Data on EM Algorithm under Rayleigh Distribution

Zhendong Li (Lanzhou University of Finance and Economics)
Mengmeng Li (Lanzhou University of Finance and Economics)



Article Info

Publish Date
01 Jun 2014

Abstract

Is EM algorithm parameter estimation under Rayleigh distribution sensitive to missing data and if it is, what extent is it? By designing computer simulation methods, contrast and analyze the results of maximum likelihood estimation with complete data and EM algorithm estimation under different missing rate in small sample. It shows that the results were almost identical when the missing rate is below 0.30, but the efficiency of EM parameter estimation gradually deteriorates as the missing rate increases. Meanwhile the results also show that the EM algorithm is sensitive to sample size and the selection of initial value. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5491

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