@Bo The discrepancy comes about because I altered your original verb: C for compatibility with my own definition of the Heaviside function: hv ...
10 hv 3 0 0 0 1 1 1 1 1 1 1 I did this simply by increasing its returned value by 1. But I did not alter the old version of ABC (ABC0) which uses it. (It does need altering). Upon restoring to your original C, I can confirm that ABC0 now returns the exact correct parameters in the absence of noise (it didn't before) ... ABC0 10 hv 3 0 1 2 and that both versions now give identical results on the few trials I've made of them, especially with the random variable X which I was using for the test... ABC0 X 98.6542 36.7969 89 ABC X 98.6542 36.7969 89 This version of X (which I've saved and will make available) is a hard test: when I plot it I can't see the step without knowing where it's meant to be. The standard deviation of the Gaussian noise is half the step height, 10. Thus the noise is capable of obliterating the information as to the exact onset of the step, so I'm impressed that ABC gets it right here, even if the estimate of B is awry in this instance. (In the absence of noise it would be 100 20 89.) With other X's I've tried, ABC makes far better estimates of B. Ian On Tue, Jul 3, 2012 at 5:17 PM, Bo Jacoby <bojac...@yahoo.dk> wrote: > The old ABC program and the new ABC program were supposed to be equivalent > algorithms, and so they should give exactly the same results for the same > test data. That is why I am bewildered by the difference. Ian did the test > and knows about the test data. > - Bo > > > > >>________________________________ >> Fra: Raul Miller <rauldmil...@gmail.com> >>Til: Programming forum <programming@jsoftware.com> >>Sendt: 16:34 tirsdag den 3. juli 2012 >>Emne: Re: [Jprogramming] Kalman filter in J? >> >>On Tue, Jul 3, 2012 at 6:08 AM, Bo Jacoby <bojac...@yahoo.dk> wrote: >>> The result changes from C=90 (correct) in the old ABC to C=89 >>> (incorrect) in the new ABC. Also the old ABC result B=41 and the >>> new ABC result B=37 should both be B=20. That is bewildering. >> >>Which test data are you using here (for X)? >> >>(Have you verified that the noise does not shift the values of the >>"best result"?) >> >>-- >>Raul >>---------------------------------------------------------------------- >>For information about J forums see http://www.jsoftware.com/forums.htm >> >> >> > ---------------------------------------------------------------------- > For information about J forums see http://www.jsoftware.com/forums.htm ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
