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From |
jverkuilen <jverkuilen@gc.cuny.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Nonlinear model using maximum likelihood |

Date |
Wed, 4 Mar 2009 08:43:43 -0500 |

Not sure if this helps, but what error distribution are you using? ML is going to need a likelihood which requires you to pick an error model, but you only have a mean structure. -----Original Message----- From: "Magnus Soderberg" <Magnus.Soderberg@unisa.edu.au> To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> Sent: 3/3/2009 5:39 PM Subject: st: Nonlinear model using maximum likelihood Dear All, I want to estimate the following nonlinear function: Y = b0 + b1*exp(b2*x1)*b4*x2*x3 + Xb Where b0 to b3 are parameters (b vector of parameters), x1 to x3 variables (X a vector of variables). I could estimate this by using the Stata command nl, but I want to use ML. There is a similar problem and a solution posted at http://www.stata.com/support/faqs/stat/nl_ml.html which looks like program mlnexpgr version 10 args lnf b1x b0 sigma tempvar res quietly gen double `res' = $ML_y1 - `b0'*(1-exp(-`b1x')) quietly replace `lnf' = -0.5*ln(2*_pi)-ln(`sigma')-0.5*`res'^2/`sigma'^2 end ml model lf mlnexpgr (b1: rep78 = headroom, nocons) (b0:) (sigma:) ml max I guess my problem is the specification of the "ml model"-line but despite numerous attempts I can't get a reasonable output. Does anyone know how to do this? All the best, Magnus * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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