Hi Luca a Bayesian version of multiple regression would also be very welcome and much appreciated in the future

Thanks Marcin . I'll wait hopefully for a menu driven version in the Gretl UI.

Am 15.08.2023 um 14:59 schrieb Brian Revell: > Thanks Marcin . I'll wait hopefully for a menu driven version in the > Gretl UI. Well, Luca also has another package called "BayTool", and you may be interested in the included function BayLinMod(). Admittedly the GUI currently still is a little rudimentary, but maybe you could give it a try and report back. Apart from that, at the risk of sounding repetitive or annoying, the question is why you want to use Bayesian regression. My impression is that 90% of the applications just want to have shrinkage and regularization that Bayesian stuff gives you "for free". The frequentist alternative these days would be Lasso and Elastic Net, which gretl offers natively with its "regls" functionality, and with a super-nice GUI. Of course, if you truly have an idea about the prior distribution, or if you want to use it for teaching or for comparison, then a Bayesian regression method is useful, and your request is perfectly legitimate. thanks sven _______________________________________________ Gretl-users mailing list -- gretl-users(a)gretlml.univpm.it To unsubscribe send an email to gretl-users-leave(a)gretlml.univpm.it Website: https://gretlml.univpm.it/postorius/lists/gretl-users.gretlml.univpm.it/

On 15.08.2023 16:55, Brian Revell wrote: > Hi Luca,Sven > > I would be happy to give Luca's BayTool a go though at my advancing > years, Scripting is not a skill I want nor need to develop any > expertise in. KIS is my motto. > Fair question to ask why would one want to use Bayesian regression?. > The answer is that scientists now seem to have abandoned frequentist > statistics. As my personal research is challenging work that fisheries > scientists are doing on salmon stock estimation who do not publish > their underlying coefficient estimates, they just publish graphs of > their 10 year Bayesian trends in official statistics with 5 year > projections and very wide unsurprisingly (in)credible intervals. I am > keen to replicate their results and examine their robustness. I have > the same data from official published statistics and know that most of > the trends they fit to the 10 year river data sets are not > statistically significant from zero from frequentist standard log > linear regression. > In summary, it is about identifying your opponent's weaknesses from > the inside Well, since prior plays a non-negligible role, so as Sven said: do you have a "true" prior or you just want to use some data-driven (like Zellner's g)? It is important, because you deal with non-stationary series with possible AR component. If so, using "standard" Bayesian set-up and tools (like g-prior with with analytical solution for posterior moments) may be misleading. So, I would advise to follow: 1. Approach developed in late 90-ties in: Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169. 2. Setup based on g-prior proposed by us in: Błażejowski M, Kwiatkowski J, Kufel P. BACE and BMA Variable Selection and Forecasting for UK Money Demand and Inflation with Gretl. Econometrics. 2020; 8(2):21. https://doi.org/10.3390/econometrics8020021 Unfortunately, in both cases using GUI-based tool is not possible. But we (I mean Jacek Kwiatkowski and I) would help, if you're interested. Marcin -- Marcin Błażejowski _______________________________________________ Gretl-users mailing list -- gretl-users(a)gretlml.univpm.it To unsubscribe send an email to gretl-users-leave(a)gretlml.univpm.it Website: https://gretlml.univpm.it/postorius/lists/gretl-users.gretlml.univpm.it/