On Fri, Mar 7, 2014 at 2:01 PM, Vijay Desai <vijay.de...@gmail.com> wrote:
> It is actually commodities futures data.
>
> Another way to handle missing data could be to estimate covariance
> matrix by ignoring the missing values and then determine eigenvectors
> of the covariance matrix to obtain principal components.
>
I'm dealing with similar issues in macroeconomics/forecasting (diffusion
indexes, factor analysis). I'm using pandas and imputing some values before
doing dimension reduction via moving average or Kalman smoother. YMMV.
Skipper
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