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Hello,

Perhaps what you're looking for is the Model::innov procedure.

Hello, Which software are you using to import the GraphML file generated by EViews? Unfortunately, as with many data formats in the XML family, GraphML is more a syntactic specification than a semantic specification. By this I mean that while a GraphML file can store many types of information about ...

Hello,

Since you've using an SVAR factorization, the impulse responses are in term of innovations to the structural variables, not the original variables, e.g. government expenditure or GDP. By construction, the one S.D. structural innovations and the one unit structural innovations are identical.

Hello, For this scenario, the documentation of the 'c' parameter is a bit misleading. Elaborating on my answer (3) above, the termination criterion actually examines the trust region size associated with each quasi-Newton step, ending the algorithm when the trust region shrinks below the value of th...

Hello, Let me try to address your three main points... (1) As of EViews 10, the speed vs. accuracy general option no longer applies to state-space estimation via FIML w/ BFGS. Formerly, that option did select between Taylor series order, basically either 2-point or 4-point numeric derivatives (with ...

Hello, More in-depth answers to all of your questions can be found in the EViews documentation for VARs, but to summarize, (1) unrestricted reduced-form VARs are estimated by OLS, (2) the LRE statistic is the Edgeworth expansion correction form of the LM test, and (3) the LM test is the Breusch-Godf...

This all depends greatly on your workflow and Git setup, but for this example suppose we have a local Git repository with the "master"/"main" branch and a "dev" branch. We want different versions of an addin registered in EViews depending on which branch is currently ac...

Hello, Addressing your last point first, stochastic innovations do interact with ARMA errors as you'd expect. Add factors are the oddity. In effect, residuals/innovations are determined before add factors are applied, so add factors don't propagate through ARMA terms. Your approach for implementing ...

My apologies, I pasted a genr expression for the calculation instead of a scalar context expression. Just replace to two @date references with @now... %mydate = @datestr(@datefloor(@now, "y") + 6 - @mod(@datepart(@datefloor(@now, "y"), "w") + 1, 7), "mm/dd/yyyy&quo...

Hello,

I believe this will work:

A quick note, addin registration is available programmatically. You could for example, write your own addin that switched the registration of other addins between their official and development versions, or even use a git hook to trigger the switch.

Hello,

Sorry your post escaped my notice earlier. Unfortunately, add factors are not treated as innovation shocks even in stochastic solves and there are no options for altering this behavior.

Hello,

Using the message window, the parsing loop of two posts back could be modified to look for the individual "Dropped add factor series " lines and extract them all that way.

I knew you'd ask that. In which case, to avoid parsing each specification for the first variable name perhaps it's best to include an add factor on all equations, thus the set of dropped add factors will match the set of modified equations.

Another good candidate for a new data member. Otherwise, a brief loop can extract the information... logmode l create u 1 ' Create a trivial model with 50 equations. model m for !i = 1 to 50 m.append x!i = y!i next m.addassign @all ' We're going to flip the first 25 equations. for !i = 1 to 25 %tmp ...