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Re: st: maximum likelihood no observations error


From   Nick Cox <njcoxstata@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: maximum likelihood no observations error
Date   Wed, 13 Mar 2013 07:58:38 +0000

-error 2000- means values all missing, so if the problem is not in your input data, it presumably is within your program. My suggestion was to insert one or more -list- commands within your program.

Nick

On 13 Mar 2013, at 00:24, andylaustata <andylaustata@126.com> wrote:

Thanks for your advice Nick, and sorry for my thoughtlessness. Poi (2002) stands for "Poi, B. P. 2002. From the help desk: Demand system estimation. Stata Journal 2(4): 403--410". Also, I have double checked all the variables that I used and none of them has any missing values.

Besides, many apologies to anyone who might have considered helping me, but found it impossible to implement my ado program, because I did not send my do code in the first place. So, I am copying my do code here. As you can see, the do code will load food.dta into your stata from http://www.stata-press.com/data/r11/food. So, expect for some copying and pasting, it is all ready for anyone interested enough to quickly run my code and see how the problem comes up.

Cheers,
Ou

use http://www.stata-press.com/data/r11/food, clear

glo NEQN = 4   /* Number of equations. */

ml model d0 RDS1 () /beta_v /theta_v /ga_v1 /ga_v2  /*
*/ /ga_v3 /ta_v1 /ta_v2 /ta_v3 /et_v1 /et_v2 / et_v3

ml check

ml search

ml maximize





At 2013-03-12 20:17:21,"Nick Cox" <njcoxstata@gmail.com> wrote:
Generic advice on Statalist, which you should have read in the FAQ.
Please give full references, not minimal references such as Poi
(2002).

Specific advice on your problem. Even experienced programmers often do
not have much success in just looking at a program to find bugs. It's
best to be proactive. -list- the data at some point and then identify
what is not present that should be, or missing. If your real dataset
is big, it might be best to test the program on a small subset.
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