On Mon, 9 Oct 2017, Sven Schreiber wrote: > Am 09.10.2017 um 12:07 schrieb Sven Schreiber: >> Am 07.10.2017 um 17:17 schrieb Allin Cottrell: > >>> Thanks for the offer, but this is now fixed in git and snapshots. The >>> thing is that for forecasting we need the "gross" MIDAS coefficients >>> (hfslope, if any, times the weights implied by the hyperparams, for >>> each midas term). >> >> I'm not sure if this is now correct, I seem to be getting some strange >> results for the Umidas case, where I _believe_ they were different (more >> plausible) before. I'll have to check, and will report back. > > Well, for example I am getting this bogus type of estimation output with > yesterday's snapshot: > > <output> > === normalized exponential Almon === > Konvergenz erreicht nach 67 Iterationen > > Modell 4: MIDAS (NKQ), benutze die Beobachtungen 1991:4-2009:4 (T = 73) > L-BFGS-B mit bedingten KQ benutzt > Abhängige Variable: dep > > Schätzung Std.-fehler t-Quotient p-Wert > ------------------------------------------------------------- > const 0.00310599 0.000813343 3.819 0.0003 *** > dep_1 −0.164985 0.118316 −1.394 0.1682 > const 0.277335 0.0991822 2.796 0.0069 *** > ... > </output>
Can you tell me what the midasreg specification looks like? I'm not seeing anything like that in the examples I'm running, but I guess they're not general enough. Allin
