I am trying to understand the mathematics behind estimating the covariance matrix for a set of observations with missing data entries (or NaN).
I would like to do this without deleting rows with missing entries or without using post-hoc smoothing to ensure that the covariance matrix is positive semi-definite. How might I do this?
I know that one method would be imputation (Missing data and covariate analysis), but what other methods are there. Thanks a lot for any insight!