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I have completed grading PS4. There is some issue about a common mistake I want to bring to your attention:
When calculating the estimated variance covariance matrix of the estimates, results.hess_inv is not a ndarray but a scipy.optimize.LbfgsInvHessProduct object, which will interpret '*' as dot multiplication instead of pointwise multiplication, thus generating irregular VCV result. Here we should use results.hess_inv.todense() * OffDiagNeg, i.e., transform it to a dense matrix, and then do the pointwise multiplication. @rickecon
Please don't hesitate to send me an email or come to my office hour if you have any question regarding your PS4's grades.
Best,
Winston
The text was updated successfully, but these errors were encountered:
Hi all,
I have completed grading PS4. There is some issue about a common mistake I want to bring to your attention:
When calculating the estimated variance covariance matrix of the estimates, results.hess_inv is not a ndarray but a scipy.optimize.LbfgsInvHessProduct object, which will interpret '*' as dot multiplication instead of pointwise multiplication, thus generating irregular VCV result. Here we should use results.hess_inv.todense() * OffDiagNeg, i.e., transform it to a dense matrix, and then do the pointwise multiplication. @rickecon
Please don't hesitate to send me an email or come to my office hour if you have any question regarding your PS4's grades.
Best,
Winston
The text was updated successfully, but these errors were encountered: