12 citations · 42 across the 12 of their papers we have counts for
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stat.CO2013
Full information maximum likelihood estimation in factor analysis with a lot of missing values
Kei Hirose, Sunyong Kim, Yutaka Kano +3
We consider the problem of full information maximum likelihood (FIML) estimation in a factor analysis model when a majority of the data values are missing. The expectation-maximiza…
stat.ME2013★ 1 cited
Estimation of oblique structure via penalized likelihood factor analysis
Kei Hirose, Michio Yamamoto
We consider the problem of sparse estimation via a lasso-type penalized likelihood procedure in a factor analysis model. Typically, the model estimation is done under the assumptio…