An EM algorithm for regression analysis with incomplete covariate information
Regression analysis is often challenged by the fact that some covariates are not completely observed. Among other approaches is a newly developed semiparametric maximum likelihood (SML) method that requires no parametric specification of the selection mechanism or the covariate distribution and that...
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Published in | Journal of statistical computation and simulation Vol. 77; no. 2; pp. 163 - 173 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Taylor & Francis
01.02.2007
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Online Access | Get full text |
ISSN | 0094-9655 1563-5163 |
DOI | 10.1080/10629360600565202 |
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