blind analysis; hierarchical models

In stars group meeting, we discussed two hierarchical models of the Gaia TGAS data. Keith Hawkins (Columbia) is building a model of the red clump stars; he finds that if he selects red-clump stars carefully, they are very good standard candles. His hierarchical model determines this and also de-noises the parallaxes for them. Boris Leistedt (NYU) went even further and deconvolved the full color-magnitude diagram, though with a baroque hierarchical model that includes a highly parameterized model for the density of stars in color–magnitude space.

In cosmology group meeting, a lot happened, with Josh Speagle (CfA) talking about next-generation photometric redshifts, Mike Blanton (NYU) talking about the huge NSF proposal we are putting in at NYU around physics and data science, and David Spergel (Flatiron), Blanton, and me arguing about blind analyses. The latter subject is rich with issues. We want (and need) exploratory data analysis, but we also want (and need) secure statistical results without p-hacking, forking paths, and so on. There was disagreement among the group, but I argued that you can have it all if you design right. There are interesting conflicts with open science there.

I also met with Francisco Villaescusa (Flatiron) to talk about work on neutrinos in large-scale structure. He promised me some papers to read on the subject.

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