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In the edit box you only enter the name of the vector object i.e. starting_values

If you click Add-ins->Manage add-ins-> select the star add-in and then Docs the add-in documentation will appear (now is attached in the first comment just in case). You have to create a vector of size 5 or greater. vector(5) starting_values=1 In this case all the starting values will equal one, if ...

Question, this is to show that spurious regressions have a high R2? wfcreate test a 1960 2000 scalar r2 = 0 series y1=0 series y2=0 group g y1 y2 while r2 < 0.8 smpl 1961 @last y1 = y1(-1) + nrnd y2 = y2(-1) + nrnd smpl @all equation eq.ls y1 c y2 scalar r2 = eq.@r2 g.line y1 y2 wend freeze(gr1) g.l...

Hi, STR models are nonlinear in parameters so to estimate them one must use an optimization algorithm, the vector object for starting values is a vector object that contains an starting value for each of the coefficients in the model respectively i.e. the position (1,1) in the vector corresponds to ...

Or maybe is something like this: wfcreate test a 1960 2000 scalar r2 = 0 while r2 < 0.8 series y1 series y2 y1(1)=0 y2(1)=0 smpl 1961 @last y1 = y1(-1) + nrnd y2 = y2(-1) + nrnd smpl @all equation eq.ls y1 c y2 scalar r2 = eq.@r2 group g y1 y2 g.line y1 y2 wend freeze(gr1) g.line y1 y2 g.scat linefit

The mean and the variance equations are estimated by ML simultaneously, therefore the estimates for the mean equation could change due to changes in the variance equation.

Hi, I'm programming a unit root test that requires uncorrelated residuals, for these i´m using information criteria to select the optimal lag length. The problem is with the command @hq, when i try to save the hq criteria in a scalar or in a control variable the following error appears "@HQ is ...

If you are interested in a shot-run cycle you can estimate the spectrum by months or even by weeks as follows.



Where your week contains 1250 data points and w!i is the i -th week.

Hi, If you are working with 100.000 observations the add-in will not work. However if you click options-->General options-->Advanced system options and change the memory reserved for windows to 200 you will probably can work with 12000 observations (in a 32 bit version). Increase the temporal aggreg...

The paper seems interesting. I don´t know what you mean exactly by the short-run effects, but you can estimate an Error Correction Model using the Engle-Granger procedure (from what I saw you have two variables CDS and bonds) and save the stationary error correction mechanism, then using the add-in ...

Do you check the add-in documentation? I provide two examples in there, one with simulated data and the other with USA inflation. The estimated model with the add-in can forecast if you choose LSTAR or ESTAR models, but if you choose LSTAR-D or ESTAR-D model it can not given that you need the transi...

This thread is about the Smooth Transition Regression (STR) add-in which performs testing, estimation and evaluation of STR models. The testing procedures includes the specific alternatives: LSTR, ESTR, LSTR-D and ESTR-D, transition variables significance and adequacy between STR structures. For the...

The cumulative spectrum could be calculated simply with the command @cumsum(%spectrum_name). The test sounds interesting but it is not in my plans, sorry.

Best regards.

Nicolas.

Hi lofficer,

The add-in only performs univariate spectral analysis, in fact I´m working on a cross spectral analysis add-in I belive it will be ready in a couple of months.

I think that the sinusoidal function that you showed can be expressed as: A1*Cos(2pit/365)+B1*Sin(2pit/365) Where Alpha_7=(A1^2+B1^2)^(1/2) and Alpha_8=tan^-1(-B1/A1), which are the amplitude and the phase shift in radians. Therefore, you can perfom the estimation by list as: @cos(2*@acos(-1)*@trend...