This is the fourth and final blog on the use of constraints in the modelling and forecasting of mortality. The previous three blogs (here, here and here) demonstrated that there is no need to worry about which linear constraints to use: the fitted values of mortality and crucially their forecast values always come out the same.
When fitting a statistical model we want two things as a minimum:
I'm a statistician so I worry about standard errors just as much as I worry about point estimates. My blog Up close and intimate with the APCI model looked at the effect of different constraints on parameter estimates in models of mortality. This blog looks at the effect of constraints on the standard errors of the parameter estimates.