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a bug in @modvar function?
Dear Ferreters:
I am trying to compute the variance for a time series. The @modvar
transformation works well for the grid points when there were no missing data.
However, if there is a missing point in the time series, I ran into trouble.
Here is a sample of what I got
yes? let skv = sktemp[gt=month_reg@modvar]
yes? list/l=1:12 skv
SKTEMP[GT=MONTH_REG@MODVAR]
Y: -0.03
DATA SET: /home/aegir2/muyin/cdf/tovs_monthly_80-98.cdf
-0.03
33
16-JAN / 1: 5.910E+08
15-FEB / 2: 5.710E+00
17-MAR / 3: 8.167E+00
16-APR / 4: 1.661E+01
16-MAY / 5: 2.528E+00
16-JUN / 6: 1.534E+00
16-JUL / 7: 6.520E+00
16-AUG / 8: 5.164E+00
15-SEP / 9: 3.358E+00
16-OCT / 10: 6.217E+00
15-NOV / 11: 7.806E+00
16-DEC / 12: 4.575E+00
It is obvious that the result for Jan is not right. Then I used the @modngd
transformation, and found for Jan, the answer is 18, well for the rest of the
months is 19. So if I specifically get rid of the bad values by using @sum,
@ngd together, I can get a correct answer, which is 7.017 in this case. I was
surprised to find this as I thought Ferret will not include the bad values in
the calculation, whici is true for the functions like @sum, and @ave, etc... Why
not in @modvar?
Is there a way to solve this easily?
Thanks for the help!
Muyin
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