On Fri, 12 Jul 2019, Sven Schreiber wrote: > Am 12.07.2019 um 16:15 schrieb Allin Cottrell: > > Neither stata nor R reject this specification, but the "arguably > > strange" output from gretl is indeed an artifact of sub-par numerical > > precision in the unbalanced case using Cholesky decomposition. I've > > switched to QR for this task and we now show something similar to > > stata: > > ... > > coefficient std. error t-ratio p-value > > ------------------------------------------------------- > > const 5.12318 0.00000 NA NA > > INDOUTPT 0.00000 0.00000 NA NA > > > > Mean dependent var 5.123181 S.D. dependent var 2.678095 > > Ah, very good, this looks much "better", thanks. > > > foreign language=stata --send-data=L > > xtset unit time > > > > foreign language=R --send-data=L > > Something else: BTW, the guide mentions that --send-data is not > available with Ox, but is silent for the Python case. Actually Artur and > I are working (not too hard) on more tools for passing stuff to Python, > but enabling --send-data would also be nice. What Python/numpy functions > would you need to make this work?
Basically just a CSV reading function -- and presumably a target structure that handles variable names, to make a distinction with just sending data in matrix form. Allin _______________________________________________ Gretl-devel mailing list -- gretl-devel@gretlml.univpm.it To unsubscribe send an email to gretl-devel-le...@gretlml.univpm.it Website: https://gretlml.univpm.it/postorius/lists/gretl-devel.gretlml.univpm.it/
