Hello Allin, I think there is a bug into laggenr_from_to or i don't know to use it. when you call it twice on 2 different id of variable(already stored into Z), it does restart the position of the returned list. For example : listlag1 = laggenr_from_to(1, 1, 50, &m_Z, m_datainfo, &err); listlag2 = laggenr_from_to(2, 1, 50, &m_Z, m_datainfo, &err); return the same numbers into listlag1 and listlag2.
I tried to fix myself the problem but i'm going to sleep. so i stop not far further than get_transform() (called by laggenr, called by laggenr_from_to) 2010/5/4 denis joubert <denis.joubert(a)gmail.com>: > 2010/5/4 Allin Cottrell <cottrell(a)wfu.edu>: >> >> On Tue, 4 May 2010, denis joubert wrote: >> >>> 2010/5/3 Allin Cottrell <cottrell(a)wfu.edu>: >>> > The test libgretl was using for "weights all zero" was not really >>> > appropriate: it was that the sum of squares of the weight series >>> > equals machine zero. I've now modified this in CVS and your >>> > example runs. (The weights are extremely small, but not literally >>> > zero.) >>> >>> thanks, i will get the cvs version :) >>> > >>> > However, the example is rather odd and this may explain gretl's >>> > complaints. The auxiliary regression for hsk estimation produces a >>> > perfect fit with the original dataset (T = 226), since you have >>> > 151 usable observations and 151 regressors (75 lags, 75 squares of >>> > lags, plus constant). Adding another observation gives one degree >>> > of freedom to the auxiliary regression, which seems to help >>> > matters. >>> >>> the 151 observations with 151 regressors is only an example of the >>> problem i got, with 210 observations or more i got the same problem (I >>> added 1 observations at a time, and more I add observations more the >>> problem shows up) >>> >>> does it mean i don't need to use hsk and should use only the auxiliary >>> regression function in order to predict next values ? >> >> No, the auxiliary regression is predicting the error variance, not >> the dependent variable. I wonder, though, why you reckon you need >> 75 lags in this model (other than, perhaps, to stress-test >> libgretl!). > > 75 was a bit to stress libgretl (i stressed libgretl with 100 lags the > first time i used it). > But the datas are very hard to predict correctly, i was trying > predicting using 100 lags with gretl gui, > the datas are made from others and can be partially reversed. (the > informations alone are very hard to be correctly predicted) > > But i successfully predicted some informations about the informations > which made the datas correctly This attemps was not serious. > So now i do the tries as a clockwork (but i tried 75 in order to > reduce the amount of informations if it does work too i will reduce > the number of lags). this try is connected this time to machine > learning algorithm in order to recover the basis informations (the > first time it was made with my brain and hands). > >> >> Allin Cottrell >> _______________________________________________ >> Gretl-users mailing list >> Gretl-users(a)lists.wfu.edu >> http://lists.wfu.edu/mailman/listinfo/gretl-users >> >
