mvnorm_fill_missing: Fill missing multivariate data based on known mean vector and...
In ashiklom/mvtraits: Fit multivariate models to partially missing trait data

Fill missing multivariate data based on known mean vector and covariance matrix

1	mvnorm_fill_missing(dat, mu, Sigma, setup = NULL)

`dat`	Data matrix (observations in rows, variables in columns) with missing data as NA
`mu`	Mean vector. Must be length `ncol(dat)`
`Sigma`	Covariance matrix. Must be dimensions `ncol(dat) x ncol(dat)`
`setup`	Information about missingness pattern, as returned by `setup_missing()`. If missing, it will be calculated. When running this function many times on data with the same missingness pattern, run `setup_missing()` once first to make this calculation more efficient.