All:
I have a SQlite database where I have stored some verification data by date
& time (cycle Z/UTC), lead_time as well as type, duration, etc. I would
like to analyze & plot the data as monthly averages. I have looked at a
bunch of examples which use some combination of zoo and aggregate, but I
have not been able to successfully apply bits and pieces from the examples
I have found. Any help is appreciated. BTW, I calculate mae (mean absolute
error), mse (mean squared error), me (mean error), and other measures
obtained by using the R verification package.
The example below is limited to 20 records and shows lead_time, r_squared,
(forecast) cycle, fcst_date (forecast date) -- the full data set is just
over 2 years of daily data with 3 forecast cycles (00Z, 12Z, and 18Z) daily.
>From my query, below) how do I construct an appropriate data structure to
analyze & plot the data as monthly averages?
Regards,
Tom
> q<-dbGetQuery(con,"select lead_time,r_squared,cycle,fcst_date from
verify_table where duration=6 limit 20")
> q
lead_time r_squared cycle fcst_date
1 6 5.405095e-02 00 07/31/2010
2 12 5.521620e-06 00 07/31/2010
3 18 1.565910e-04 00 07/31/2010
4 24 8.646822e-02 00 07/31/2010
5 30 1.719604e-02 00 07/31/2010
6 36 5.768113e-04 00 07/31/2010
7 42 2.501269e-06 00 07/31/2010
8 48 6.451727e-02 00 07/31/2010
9 6 2.857931e-01 12 07/31/2010
10 12 1.138635e-01 12 07/31/2010
11 18 2.225503e-02 12 07/31/2010
12 24 1.182031e-03 12 07/31/2010
13 30 8.841142e-04 12 07/31/2010
14 36 1.082490e-01 12 07/31/2010
15 42 1.502887e-05 12 07/31/2010
16 48 NA 12 07/31/2010
17 6 8.689588e-02 00 08/01/2010
18 12 5.884336e-04 00 08/01/2010
19 18 2.219316e-07 00 08/01/2010
20 24 3.960752e-02 00 08/01/2010
--
Thomas E Adams
National Weather Service
Ohio River Forecast Center
1901 South State Route 134
Wilmington, OH 45177
EMAIL: thomas.ad...@noaa.gov
VOICE: 937-383-0528
FAX: 937-383-0033
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