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The patch has been released.

Apologies. Found the issue and we will get a fix out shortly. I'm very sorry for the inconvenience. Thanks again for your help.

Thanks for the additional info. I'll get back to you as soon as possible.

If you change your option to smoothing, you match the TSP results (note that your TSP command smooths). ss1.makestate(t=smooth) f* [edit: However, in this case the smooths and the filtered should align. All of the reported one-step ahead and smoothed look fine and all of our test cases report that t...

Could you please repost the spreadsheet if possible?

We are forming symmetric CIs under the assumption of asymptotic normality, even in the case of bootstrapping, as the latter is for the coefficient covariance and not for the coefficient distribution.

Funny, I'm not seeing that behavior. Estimation from 1953 to 2018 gives estimates with 789 observations for ARMA-ML. Dynamic forecasting for 2019 gives values starting at -1.04 and ascending gradually to -0.55 As to the behavior that you reported... I'm not saying that this is what happened, but not...

It should work. Can you give us a bit more detail on precisely what you are doing, what you expect, and what you are seeing.

Thanks.

Two parts to the question. First, you can add a confidence ellipse as a layer to the scatterplot. From the interface, click on the graph, and select the desired confidence ellipse in the Fit Line combo. In command form group grp1 x y grp1.scat cellipse There are options for the computation of the el...

You can reparameterize using the @logistic or other such transformation. Simply replace the current parameter, say C(5), with @logit(C(5)). EViews will estimate the deep unrestricted parameter, while the model sees the restricted value.

Unfortunately, computing forecast standard errors for MS switching is extremely difficult and not currently supported. Support will almost certainly have to be using simulation methods, which are likely to be computationally intensive. I'll put this on the list of things to consider for future devel...

I'm don't understand the request.

Sorry to take so long. Missed seeing this one.

It will be fixed in the next patch.

Not built-in. The nonlinear nature of the estimators makes this difficult.

Have to think about this. Can you send me the workfile?