st: ML Program and ML Maximize Help

[Greg Evans <Greg.Evans@evans-corp.com>]

Hello All,
This is my first post to the listserv so please excuse any errors in my 
attempt to ask my question.  And thank you in advance for your help.

I am trying to write a maximum likelihood program to run on a panel 
dataset and am getting a "varlist required" error message.  The error 
comes at the end of the code so all steps seem to run until the ml 
maximize step.

I am following from the "ML Maximum Likelihood Estimation with Stata" 
Third Edition book (authors William Gould, Jeffrey Pitblado, and William 
Sribney).  Since the error comes at the end, after the ml maximize 
statement, I'm assuming the error is telling me I need a varlist in the 
ml maximize statement, but I could be wrong.  Based on the book, it does 
not appear that I need to specify variables in the ml maximize 
statement.  The variables, it would seem, are to be specified in the ml 
model statement, not the ml maximize statement.

Here is the text of the code:

clear
set mem 100m
set more off

use "G:\Dissertation Data\TSP Stock Data\ile.dta"

global stock

program define lesmond
	version 10.1
	args todo b lnf
	tempvar alpha1 alpha2 beta sigma last
	mleval `alpha1' = `b', eq(1)
	mleval `alpha2' = `b', eq(2)
	mleval `beta' = `b', eq(3)
	mleval `sigma' = `b', eq(4)
// MY_panel contains the panel ID
local by $stock
sort `by'
local ri_r $ML_y1
quietly {
	by `by': gen `last' = _n==_N

mlsum `lnf'= = -ln(`sigma') - (1/(2*`sigma'^2))*($ML_y1 + `alpha1' - 
`beta')^2 if $ML_y1 < 0
replace `lnf' = -ln(`sigma') - (1/(2*`sigma'^2))*($ML_y1 + `alpha2' - 
`beta')^2 if $ML_y1 > 0
replace `lnf' = ln(normal(`alpha2'-`beta')/`sigma') - 
normal(`alpha1'-`beta')/`sigma') if $ML_y1=0
if `last' == 1
}
end


ml model d0 lesmond (alpha1:) (alpha2:) (beta: ri_r=li_r, nocons) (sigma:)

ml maximize

--
~~~~~~~~~~~~~~~~~~~~~
Greg Evans
University of Georgia
Choose Happy!
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