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Support missing data in PPCA #138

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oxinabox opened this issue Jan 29, 2021 · 1 comment

Contributor

oxinabox commented Jan 29, 2021 •

edited

According to the PPCA paper

Tipping, Michael E., and Christopher M. Bishop. "Probabilistic principal component analysis." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 61.3 (1999): 611-622.
one of the key advantages of PPCA over PCA is that it can naturally handle missing data.

The method is in section 4.1 of the paper; though it's not a great decription.
It would be cool to have.

Collaborator

wildart commented Jan 29, 2021

It's more about the estimation of Gaussian model properties from the missing data, see section 11.2 in "Statistical Analysis with Missing Data",Little and Rubin, 2020.

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