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From |
"Renzo Comolli" <[email protected]> |

To |
<[email protected]> |

Subject |
Re: st: Maximum Likelihood |

Date |
Fri, 2 May 2003 10:21:38 -0400 |

Dear Deborah, I have done very little maximum likelyhood, so I am not sure I can help you fully. There is something I can tell you for sure, though. You cannot write args Li x1 x2 You must write args lnf theta1 theta2 And you must keep on doing so throughout the script. I found the book Maximum Likelihood Estimation with Stata by William Gould, William Sribney to be extremely useful (it is written for version 6.0 but ML has changed very little, if at all, since then) Suggestion to Stata: I found the description of ML in the manuals base reference (for version 7.0) too short. Just one little example, I could not find reference to the issue mentioned here. Best, Renzo Comolli -----Original Message----- [only bits of the original message] I am trying to use the maximum likelihood procedures in Stata and am getting some bizarre results that suggest that I do not fully understand how the lnf feature works. I'd be very grateful for some illumination. thanks, deborah. ------------------------------------ lf version, no constant option: program define ml_move; 1. args Li x1 x2; 2. quietly replace `Li' = ln( (1 - normprob(`x1' + `x2'))*probmax + (1 - normprob(`x2')*(1 > -probmax)) ) if $ML_y1==1; 3. quietly replace `Li' = ln( normprob(`x1' + `x2')*probmax + normprob(`x2')*(1-probmax) ) > if $ML_y1==0; 4. end; . ml model lf ml_move (leavejob = alt_ret pv_ira, nocons ) > (pension esitaxprice > jobtenure > esi spesi > age35_45 age45_55 > hispanic black race_oth > school_1-school_3 firm_x firm24 > firm25_99 occ_2-occ_7 occ_x ind_1-ind_4 ind_6 ind_x urban union > hlth_x hlth_gd hlth_fp > logann logtxinc > secondearn > kid kid2 > married female ira_x jobten_x > year84 year90 year96) > [pweight=irawgt] if age1 >= 25 & age1 <= 55 ; . ml maximize; initial: log likelihood = -30971.235 alternative: log likelihood = -21880.591 rescale: log likelihood = -20492.416 rescale eq: log likelihood = -20304.363 Iteration 0: log likelihood = -20304.363 Iteration 1: log likelihood = -17187.65 Iteration 2: log likelihood = -17036.272 Iteration 3: log likelihood = -17034.944 Iteration 4: log likelihood = -17034.944 (not concave) Number of obs = 53011 Wald chi2(0) = . Log likelihood = -17034.944 Prob > chi2 = . ---------------------------------------------------------------------------- -- | Robust leavejob | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+-------------------------------------------------------------- -- eq1 | alt_ret | 815.4468 . . . . . pv_ira | .000559 . . . . . -------------+-------------------------------------------------------------- -- eq2 | pension | .7307576 .0258399 28.28 0.000 .6801123 .781403 esitaxprice | -.0503448 .1366193 -0.37 0.712 -.3181137 .2174242 [OTHER VARIABLES SUPPRESSED] _cons | -.6282337 .0767639 -8.18 0.000 -.7786882 -.4777793 ---------------------------------------------------------------------------- * * 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/

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