On Tue, 6 Jan 2015, Summers, Peter wrote: > [T]he ordered probit thing is still there. I'm using a script with > generic notation "model4 <- probit y 0 x(-1 to -5)." I get the same > result (lagged y included) via the gui, but running your script > works as expected (no lagged y). I'll send you my data and a script > that generates the weirdness off-list.
That should now be fixed in CVS and snapshots. The spurious "extra regressors" you were seeing were not actually lags, they were dummies for some of the levels of the dependent variable; they somehow got into the mix due to failure of the algorithm that was supposed to normalize the dependent variable (that is, to transform it such that it comprises consecutive integer values starting at zero). I've replaced that algorithm with a smarter one. It should now be safe to pass a series with non-integral values as the dependent variable in ordered probit, provided it has been sucessfully marked as discrete. (I'm still not sure exactly what triggered the problem in your test case: it turned out that y having non-integral values was not a sufficient condition. But anyway the new algorithm should handle all cases.) Allin
