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Re: st: MLE: Setting Initial Values
In your -ml model- statement you specify only 4 dependent variables
(Y_Y_C, N_N, Y_N, and N_Y), while in log likelihood you use 7 ($MLy_1
till $MLy_7). Surprisingly this does not lead to an error message, but
to the model not converging. (I have made the same mistake before)
Hope this helps,
Maarten
--- Sabah Abdullah <[email protected]> wrote:
> Dear Stata Listserve:
>
> Presently I am working on MLE and was able to maximize some of my
> data
> but one of them refused to maximize the error message was could not
> find feasible values
> r(491); (see below for more details) . Hence, I tried to set initial
> values but all I am receiving are error messages. Please see below
> for
> my commands and results.
> Note I do not have any missing values. I will be grateful for any
> suggestions or comments.
>
> Regards,
>
> Sabah
> --
>
> COMMANDS:
> capture program drop double_cv_4
> program double_cv_4
> version 9.2
> args lnf xb bid
> qui replace `lnf' = ln(invlogit($ML_y6*`bid'+`xb')) if $ML_y1 == 1
> qui replace `lnf' = ln(invlogit(-($ML_y7*`bid'+`xb'))) if $ML_y2 ==
> 1
> qui replace `lnf' = ln(invlogit(-($ML_y6*`bid'+`xb')) - ///
> invlogit(-($ML_y5*`bid'+`xb'))) if $ML_y3 == 1
> qui replace `lnf' = ln(invlogit(-($ML_y5*`bid'+`xb')) - ///
> invlogit(-($ML_y7*`bid'+`xb'))) if $ML_y4 == 1
> end
>
>
> ml model lf double_cv_4 (xb: Y_Y_C N_N Y_N N_Y = rev_incm) (bid:
> bid_intl bid_low bid_high = )
> ml maximize, difficult
> ml graph
>
>
> OUTPUT:
> initial: log likelihood = -<inf> (could not be evaluated)
>
> could not find feasible values
> r(491);
>
>
>
> What I decided to do following recommendation in MLE book by Gould et
> al, 3rd edition---loading initial values from vectors:
>
> COMMANDS
> . regress Y_Y_C rev_incm sexresp_male
>
> Source | SS df MS Number of obs
> = 200
> -------------+------------------------------ F( 2, 197)
> = 2.52
> Model | .527840655 2 .263920328 Prob > F
> = 0.0827
> Residual | 20.5921593 197 .104528728 R-squared
> = 0.0250
> -------------+------------------------------ Adj R-squared
> = 0.0151
> Total | 21.12 199 .106130653 Root MSE
> = .32331
>
>
------------------------------------------------------------------------------
> Y_Y_C | Coef. Std. Err. t P>|t| [95% Conf.
> Interval]
>
-------------+----------------------------------------------------------------
> rev_incm | 2.40e-06 2.92e-06 0.82 0.411 -3.35e-06
> 8.15e-06
> sexresp_male | .0917239 .0510439 1.80 0.074 -.0089387
> .1923866
> _cons | .0652509 .0386968 1.69 0.093 -.0110622
> .1415639
>
------------------------------------------------------------------------------
>
> . matrix b0 = e(b)
>
> . ml model lf double_cv_4 (xb: Y_Y_C N_N Y_N N_Y = rev_incm
> sexresp_male) (bid: bid_intl bid_low bid_high = ) /sigma1
> > /sigma2
>
> . ml init b0
>
> . ml maximize
>
> initial: log likelihood = -<inf> (could not be evaluated)
>
> could not find feasible values
> r(491);
>
> . ml check
>
> Test 1: Calling double_cv_4 to check if it computes log likelihood
> and
> does not alter coefficient vector...
> Passed.
>
> Test 2: Calling double_cv_4 again to check if the same log
> likelihood value
> is returned...
> Passed.
>
>
------------------------------------------------------------------------------
> The initial values are not feasible. This may be because the initial
> values
> have been chosen poorly or because there is an error in double_cv_4
> and it
> always returns missing no matter what the parameter values.
>
> Stata is going to use ml search to find a feasible set of initial
> values.
> If double_cv_4 is broken, this will not work and you will have to
> press Break
> to make ml search stop.
>
> Searching...
> initial: log likelihood = -<inf> (could not be evaluated)
> searching for feasible values
>
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> >
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>
> could not find feasible values
> r(491);
>
>
> . ml query
>
> Method: lf
> Program: double_cv_4
> Dep. variables: Y_Y_C N_N Y_N N_Y bid_intl bid_low bid_high
> 4 equations:
> xb: rev_incm sexresp_male
> /bid
> /sigma1
> /sigma2
> Search bounds:
> xb: -inf +inf
> /bid -inf +inf
> /sigma1 -inf +inf
> /sigma2 -inf +inf
> Current (initial) values:
> xb:_cons 35.081399
> bid:_cons 58.844529
> sigma1:_cons 30.126179
> sigma2:_cons 73.279225
> remaining values are zero
>
> .
> end of do-file
>
>
>
>
> ***********************************************
> Ms. Sabah Abdullah
> PhD Student
> University of Bath
> Department of Economics & Int'l Dev.
> BATH
> BA2 7AY
> UNITED KINGDOM
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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*
* For searches and help try:
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