Thank you Marguerite. Looking at OUwie and OUCH/SLOUCH, i see that alpha is
estimated along the other parameters, whereas in Hansen 1997 and other
papers it is suggested that this would lead to very large standard errors.
Is that problem resolved in these functions?
Best,
Sandra.
2013/10/26
In at least the OUwie paper we spent a lot of time doing simulations to
determine this empirically (this may have been examined in other papers,
too, though none come to mind). Alpha can be estimated, but sometimes with
scarily large standard errors (but not always). This property should hold
for
FYI, we have some theory to explain why alpha has large standard errors
and in which conditions. As Brian says, it comes with a flat likelihood
with respect with alpha.
http://dx.doi.org/10.1214/13-AOS1105 or
http://www.stat.wisc.edu/~ane/publis/2013HoAne_AoS.pdf
On 10/29/2013 09:46 AM, Brian
Hi Sandra and others,
You can also assess confidence using parametric bootstrap, a procedure which we
generally recommend for all users. ouch has built-in facilities to do so (the
bootstrap() and simulate() functions in addition to update() ). I think there
are examples in my tutorial. If
The error happens after it does the calculation for the point estimates, so
it's likely happening when it starts doing the calculations to look at the
curvature at the solution (to see if it's a maximum rather than a saddle
point and to get an estimate of standard errors). Doing
OU1 -
