Thanks Will.
Below is the flow of my code
Yhat is the fitted value
Errhat is the difference between the dependent variable and the yhat
gmmdata is the data name
N <- nrow(gmmdata)
B <- 1000
store <- matrix(0,B,11)
for (j in 1:B) {
index = sample(1:N, N, replace=T)
errnew = errhat[index]
yt = yhat + errnew
objective function subroutine
gradient function subroutine
gmmiv =Optimx()
store[j,] = coef(gmmiv)
}
What I want to do is that if the convergence code from optimx for a particular
iteration is Not zero, then it should not be stored in store[j,].
Any help will be appreciated
Thank you
--------------------------------------------
On Tue, 9/15/15, Will Hopper <wjhopper...@gmail.com> wrote:
Subject: Re: [R] Drop in a Loop
Cc: r-help@r-project.org
Date: Tuesday, September 15, 2015, 2:30 PM
I
think you ought to show a small example of how the code
you're using. Are you saving results at every iteration?
In a list, data frame, etc? People likely need that to help
answer your question.
Also probably have a look the control list
argument and the save.failures option, that might be
something you're interested in.
- Will
On Tue, Sep 15, 2015 at
1:34 PM, Olu Ola via R-help <r-help@r-project.org>
wrote:
Hello,
I am doing some estimation using optimx and after each round
of estimation, I store the coefficient. However, I need to
drop the set of coefficients for which the convergence code
in optimx is GREATER than Zero. How do I go about this?
A way forward will be highly appreciated.
Thank you
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
