Peter Dalgaard [EMAIL PROTECTED] writes:
Re. the smoothed residuals, you do need to be careful about the
smoother. Some of the robust ones will do precisely the wrong thing
in this context: You really are interested in the mean, not some
trimmed mean (which can easily amount to throwing away
It is easy to spot response nonlinearity in normal linear models using
plot(something.lm).
However plot(something.glm) produces artifactual peculiarities since the
diagnostic residuals are constrained by the fact that y can only take
values 0 or 1.
What do R users find most useful in checking
Patrick Foley [EMAIL PROTECTED] writes:
It is easy to spot response nonlinearity in normal linear models using
plot(something.lm).
However plot(something.glm) produces artifactual peculiarities since
the diagnostic residuals are constrained by the fact that y can only
take values 0 or 1.
