Impact of missing data on parameter estimation algorithm of normal distribution

doi:10.1109/IMSNA.2013.6743342

LZUFE-KMS

	Impact of missing data on parameter estimation algorithm of normal distribution
	Feng, Wang 1; Shaotong, Wang 2
	2013
会议名称	2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2013
会议录名称	Proceedings - 2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2013
期号	0
页码	574-578
会议日期	2013-12-23 - 2013-12-24
会议地点	Toronto, ON, Canada
出版者	IEEE Computer Society
摘要	This paper propose a simulation approach for the parameter estimation of normal distribution, to analyze the EM algorithm with missing data under different missing rates and complete data maximum likelihood estimation. The simulation result shows that the EM algorithm and the maximum likelihood estimates are almost unanimously when the missing rate is less than 0.25, but the effect of parameter estimation of the EM algorithm gradually deteriorates when the missing rate increases. The result also shows that the EM algorithm is more sensitive to the initial value. In addition, this paper also analyzes the evaluation of the selection of initial value for EM algorithm. © 2013 IEEE.
关键词	Genetic algorithms Maximum likelihood estimation Normal distribution Sensor networks EM algorithms Maximum likelihood estimate Missing data Missing rate Parameter estimation algorithm Simulation approach
DOI	10.1109/IMSNA.2013.6743342
收录类别	EI ; CPCI
语种	英语
EI入藏号	20141617597703
文献类型	会议论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/9769
专题	兰州财经大学
作者单位	1.School of Information Engineering, Lanzhou University of Finance and Economics, Lanzhou, China; 2.School of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China
推荐引用方式 GB/T 7714	Feng, Wang,Shaotong, Wang. Impact of missing data on parameter estimation algorithm of normal distribution[C]:IEEE Computer Society,2013:574-578.