Skipper, thanks for your input.

On Fri, Mar 7, 2014 at 2:18 PM, Skipper Seabold <jsseab...@gmail.com> wrote:
> 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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