2nd lecture, with more advanced materials.
@ChrisRackauckas @jstac @thomassargent30 I moved some of the rough notes from the previous lecture to this placeholder. We can "get fancy" with uncertainty quantitficaiton, bayesian estimation of differential equations/etc. DiffEqFlux, etc. after the basic lecture is solid.
My hope was that we wouldn't need to introduce a new "model" in this lecture, and could just refer back to the previous one for the nested setup. Shutting things off as required.
For the title, I put in the "Model Uncertainty" to emphasize the economic goals (e.g. uncertainty quantification) but don't have a strong opinion.
2nd lecture, with more advanced materials. @ChrisRackauckas @jstac @thomassargent30 I moved some of the rough notes from the previous lecture to this placeholder. We can "get fancy" with uncertainty quantitficaiton, bayesian estimation of differential equations/etc. DiffEqFlux, etc. after the basic lecture is solid.
My hope was that we wouldn't need to introduce a new "model" in this lecture, and could just refer back to the previous one for the nested setup. Shutting things off as required.
For the title, I put in the "Model Uncertainty" to emphasize the economic goals (e.g. uncertainty quantification) but don't have a strong opinion.