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From |
"Lenny Stoeldraijer" <lennystoeldraijer@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: difficult ML program |

Date |
Tue, 4 Mar 2008 15:22:05 +0100 |

Hi, I'm trying to make my own maximum likelihood model, but I can't get it right. The first part looks okay (I think), but then I have to define the function which is called ua, which looks like: exp(uncc*(b+hazu)-exp(b)*survu), where b is the coefficient to be estimated. This coefficient is thus used twice but once with an exponential. So far, my code looks like this (I've left some parts out): program define myml args lnf covu lu0 lu1 lu2 ... theta1 theta2 tempvar hazu survu ua quietly gen double `hazu' = `covu'+`lu0'+dtu1*`lu1'+dtu2*`lu2'+... quietly gen double `survu' = exp(`covu'+`lu0')*(btu0+btu1*exp(`lu1')+btu2*exp(`lu2')+... quietly gen double `ua' = exp(`theta1'+uncc*`hazu'-`theta2') replace`lnf' = log(`ua') end ml model lf myml (covu: ... , nocons) (luo: ... , nocons) (lu1:...) (lu2:...) ... (theta1: uncc) (theta2: `survu'), technique(bhhh) In the code I thus have different estimates for the b (once in theta1 and once in theta2). I've tried to include a constraint (e.g. b1=log(b2)), but then I get errors (111 for example). Does anyone have a suggestion how to model this? I really appreciate any advices. Best, Lenny ps: I have the program in TSP also where it works fine. I can sent that also if it is helpful * * 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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