I have a hard time with this as a way to extend data. If it is high-dimensional it will be under-sampled. Seems better to me to measure or simulate more so that the joint distribution can be realistic. And if you can do that there is no reason to infer the joint distribution because you *have* it.
On Apr 19, 2020, at 8:18 AM, Frank Wimberly <[email protected]> wrote: Going back and forth: If you infer the causal graph from observational data you can use that graph to simulate data with the same joint distribution as the original data. Frank On Sun, Apr 19, 2020 at 9:11 AM uǝlƃ ☣ <[email protected]<mailto:[email protected]>> wrote: The *ensemble* point is the primary reason I regret not being able to parse your response to my Necker cube summarization of EricS' TLDR. It goes back to the original question of how/whether distributional conceptions better catch the unknown unknowns left dangling in the ambience. Pearl's attempts to burst "causality" into graphs, away from chains (though helping to identify chains when they do exist) is along the same line. To boot, it evokes both Gödel's interpretation of von Neumann's interpretation of Gödel's work (that it takes an infinite expression to describe a thing) and Rosen's definition of complexity (basically anything that requires an infinite number of models to describe). And, although I can't get my hands on the Rota paper EricS posted, I'm leery of relying on any phenomenology. Heidegger I trust a bit. Husserl not so much. Regardless, I don't think it's *necessary* to go that deep to grok the main point, which is that the transformation should be invertible. We should be able to flip back and forth from goo to thing such that the flipping doesn't change it. The goo we get after flipping from the things should be the same goo we had to start with. On 4/19/20 6:25 AM, Steven A Smith wrote: > My work of late (other than SimTable) has been in the realm of trying to > analyze ensembles of predictive simulations. This is a logical next step > (forward and backward propogating data and constraints as they are > recorded/discovered/postulated) across space (populations) and time. -- ☣ uǝlƃ .-. .- -. -.. --- -- -..-. -.. --- - ... -..-. .- -. -.. -..-. -.. .- ... .... . ... FRIAM Applied Complexity Group listserv Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam<http://bit.ly/virtualfriam> unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com archives: http://friam.471366.n2.nabble.com/ FRIAM-COMIC<http://friam.471366.n2.nabble.com/FRIAM-COMIC> http://friam-comic.blogspot.com/ -- Frank Wimberly 140 Calle Ojo Feliz Santa Fe, NM 87505 505 670-9918 .-. .- -. -.. --- -- -..-. -.. --- - ... -..-. .- -. -.. -..-. -.. .- ... .... . ... FRIAM Applied Complexity Group listserv Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com archives: http://friam.471366.n2.nabble.com/ FRIAM-COMIC http://friam-comic.blogspot.com/
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