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Re: st: Defining variables for the ml procedure


From   [email protected]
To   [email protected]
Subject   Re: st: Defining variables for the ml procedure
Date   Mon, 10 Oct 2005 13:47:33 -0400

Hi Ed,

Thank you for your reply.  Your Option 2 sounds very promising and I
would be very grateful for any hints and advice you might have on how
to use it.

(As I understand it, I cannot use Option 1 because the variable Z is
unobserved. Since it depends on the unknown coefficient c, the
variable Z must somehow be generated as a part of (that is,
simultaneously as) the estimation of the regression equation

y = a + b*(c*Z[_n-1] + x))

Please let me know if this is not clear, and thanks for your help!

Best Regards
Bjorn



Quoting Ed Blackburne <[email protected]>:

Bjorn,

My understanding is that you want to estimate an equation of the form
(it doesn't much matter whether it is Z or Z[_N-1] for this post):

y=a+b(cZ+x)

Is this correct?
If so, I see two options.

Option 1: Estimate y=a+dZ+bx and use nlcom to recover c:
	nlcom _b[Z]/_b[x]

Option 2: You can estimate via conditional likelihood (aka profile
likelihoods) using the undocumented hold option of ml.

If you would like a pointer at Option 2 let me know.

-Ed


On Sun, 2005-10-09 at 12:59 -0400, [email protected] wrote:
Dear Statalist,

I am trying to estimate a nonlinear regression equation using the ml
routine, and I am having problems defining one of my input variables.
 Specifically, I would like to use the recursively defined variable
Z(it):

Z(it) = c*Z(it-1) + X(it)

as an independent variable in my regression equation.  If the
coefficient "c" is known, this variable can be generated as follows:

gen Z = X
bysort group (time): replace Z = c * Z[_n-1] + X if _n >= 2

My problem is that I would like to estimate the coefficient "c" (along
with the other regression coefficients) and therefore I need to define
the variable Z(it) "within" the program itself.

It seems, however, as if the "by" command and the "if" command are not
allowed when specifying variables in the ml programs.  I would be most
grateful if anyone would have any ideas on how to do this.

Thank you for your help.

Best
Bjorn



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