Statistical learning in models made of modules

A more in-depth tour of our paper, by Pierre!

Statisfaction

2017-09-modularization Graph of variables in a model made of two modules: the first with parameter theta1 and data Y1, and the second with parameter theta2 and data Y2, defined conditionally upon theta1.

Hi,

With Lawrence Murray, Chris Holmes and Christian Robert, we have recently arXived a paper entitled “Better together? Statistical learning in models made of modules”. Christian blogged about it already. The context is the following: parameters of a first model appear as inputs in another model. The question is whether to consider a “joint model approach”, where all parameters are estimated simultaneously with all of the data. Or if one should instead follow a “modular approach”, where the first parameters are estimated with the first model only, ignoring the second model. Examples of modular approaches include the “cut distribution“, or “two-step estimators” (e.g. Chapter 6 of Newey & McFadden (1994)). In many…

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2 Responses to “Statistical learning in models made of modules”

    • Pierre Jacob Says:

      Thanks, I’ll have a read.

      I hope you might consider some of the references in our paper relevant to yours, if not our paper itself.

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