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Compare the above results (showing NaN T0) with that of --every=2. The weird thing is that it doesn't seem to be a problem now with the amount of data (try --tfinal=1500 --every=2 which doubles the data from the above case and contains roughly the same number of points as --tfinal=1000 --every=1). The problem genuinely seems to be the high resolution data.
The text was updated successfully, but these errors were encountered:
First two refs indicate that instability due to round-off errors in the time recursion may be the culprit. Current best guess for a more-stable, Burg-like algorithm might be found in http://www.citeulike.org/user/RhysU/article/11863500 (and similar works by Strobach) refered to as PORLA4.
So much for #3 being closed-- still seeing problems on test cases like...
Compare the above results (showing
NaN T0
) with that of--every=2
. The weird thing is that it doesn't seem to be a problem now with the amount of data (try--tfinal=1500 --every=2
which doubles the data from the above case and contains roughly the same number of points as--tfinal=1000 --every=1
). The problem genuinely seems to be the high resolution data.The text was updated successfully, but these errors were encountered: