Nobody answered, but this is what I did.
I used an iterative poor man's imputation and filled in the data with a
single value at each iteration. My covariance matrices and variance will
be a little underestimated, but it'll do for me at this stage of this
project.
I iteratively filled in the
Hello,
I have been googling for 2 days and I cannot find the answer in
previous posts.
I have a set of d-dimensional data elements (d=11 .. 14), each data
point can be censored at different values both
Lower-limit and upper limit.
N = 2000 sets of vectors of
D=11 data points per vector.
