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
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