[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Magnus Soderberg <Magnus.Soderberg@unisa.edu.au> |

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

Subject |
st: Nonlinear model using maximum likelihood |

Date |
Wed, 4 Mar 2009 09:09:18 +1030 |

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/

- Prev by Date:
**st: Maximize a function that contains an integral** - Next by Date:
**Re: st: ENDESA** - Previous by thread:
**st: Maximize a function that contains an integral** - Next by thread:
**RE: st: Nonlinear model using maximum likelihood** - Index(es):

© Copyright 1996–2016 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |