[SciPy-user] fill a timeseries with masked data by correlation from another series

[Marco Tuckner]

Hello,
on the timeseries Scikit wiki it is shown how to perform simple operations on
two or more time series of the same frequency such as adding them [1].

Is it also possible to perform mathematical and statistical operations on two or
more timeseries with same frequencies?

I would like to correlate two (or more timeseries) to estimate invalid and
masked values in one series based on the values of another complete series using
the correlation coefficient.
How can I to that?

I tried this without successs:
### CODE ###
In [22]: scipy.stats.corrcoef(series,modseries)
/usr/lib/python2.5/site-packages/maskedarray/core.py:1520: UserWarning: Warning:
converting a masked element to nan.
  warnings.warn("Warning: converting a masked element to nan.")
Out[22]: 
array([[                  nan,                   nan],
       [                  nan,                   nan]])

######

Furthermore I like to calculate other tests like t-test, chi-test,
Kolmogorov-Smirnof on the two sets and get distribution parameters (RMSE, MBE,
STD) for each series.
How can this be done?

Thank you in advance for your help.

Regards,
Marco

[1]: Operations on TimeSeries -
http://scipy.org/scipy/scikits/wiki/TimeSeries#OperationsonTimeSeries