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An efficient algorithm for computing covariance matrices from data with missing values

 

作者: Laszlo Engelman,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1982）
卷期: Volume 11, issue 1  

页码: 113-121

 

ISSN:0361-0918

 

年代: 1982

 

DOI:10.1080/03610918208812248

 

出版商: Marcel Dekker, Inc.

 

关键词: computing covariance and correlation matrices;data with missing values;cost of computing;FORTRAN code;ALLVALUE covariance;COVPAIR covariance;ALLVALUE correlations;COVPAIR correlations;CORPAIR correlation

 

数据来源: Taylor

 

摘要:

An algorithm for computing covariance and correlation matrices from data with missing values is presented. In terms of the number of operations performed (hence CPU time used) this algorithm is more efficient than that used by most statistical computing packages. CPU time efficiency is attained without undue increase in the number of input/output operations or memory space requirements.

 

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