* Look at STARPAC ftp://ftp.ucar.edu/starpac/ and Statlib
http://lib.stat.cmu.edu/ for more ideas

* Try using the Kahan summation formula to improve accuracy for the
NIST tests (see Brian for details, below is a sketch of the algorithm).

      sum = x(1)
      c = 0
      
      DO i = 2, 1000000, 1
         y = x(i) - c
         t = sum + y
         c = (t - sum) - y
         sum = t
      ENDDO

* Prevent incorrect use of unsorted data for quartile calculations
using a typedef for sorted data (?)

* Rejection of outliers

* Time series. Auto correlation, cross-correlation, smoothing (moving
average), detrending, various econometric things. Integrated
quantities (area under the curve). Interpolation of noisy data/fitting
-- maybe add that to the existing interpolation stuff.What about
missing data and gaps?

   There is a new GNU package called gretl which does econometrics

* Statistical tests (equal means, equal variance, etc).

