Constructing partial least squares model in the presence of missing data
Virtually all methods of data analysis are plagued by problems with missing data, and partial least squares are no exception.This work contributes to knowledge by critically examining ways of handling missing data in the estimation of Partial Least Squares Models. The experiments are performed using...
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| Format: | Article |
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American Scientific Publishers
2015
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