**announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

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

From |
Aljar Meesters <aljar.meesters@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Non-linear model + More parameters than variables + -ml- |

Date |
Fri, 3 May 2013 18:38:21 +0200 |

Dear Miguel, In an earlier post of you I have suggested to pass your independent variables as if it was dependent so you could run your program with minor adjustments. Yet, I also suggested to use non linear least squares. You replied that you have ran into convergence problems by using non linear least squares, so I can see why you want to continue with maximum likelihood (although I suggest that you should check if the ml estimates give you a global maximum by using different starting values, since convergence is apparently problematic). In order to get this model running you can use: ml model lf datos6mean (theta1:vdmean=) (theta2:vlagmean=) (theta3:) (theta4:) (sigma:) ml maximize basically the idea is that between the () you start with a name of the parameter than a double dot, the name of a variable that you can obtain via $ML_y* and the number of () gives you the number of parameters that you, in your case, can obtain via `theta1', `theta2', etc. This is a bit of a hack and I have suggested it to get you started with the idea that you would use -nl-. You may want to look at method-d0, d1, or d2 evaluators, if you want to proceed with using -ml-, since these are more suited for your problem. Best, Aljar 2013/4/30 Miguel Angel Duran <maduran@uma.es>: > Hi, Statalisters. I am stuck with a problem. I have been able to solve part > of it (with your help), but not the following. > One of the versions of my model is not linear and quite complex. This is it > (x and y are variables, and thetas are parameters), > > y=[theta1+theta2*(x/theta3)^theta4]*[1-(x/theta3)] > > To estimate it using -ml- I have used this program (assuming that residuals > are normally distributed): > > program datos6mean > version 10.1 > args lnf theta1 theta2 theta3 theta4 sigma > quietly replace `lnf' = ln(normalden($ML_y1, > (`theta1'+`theta2'*($ML_y2/`theta3')^`theta4')*(1 - ($ML_y2/`theta3')), > `sigma')) > end > > Nevertheless, I do not know how to write the command -ml model lf > datos6mean- in order to indicate Stata that there are just two variables > (that I have introduced as if both of them were dependent variables), that > there is no linear part in the model, but there are four parameters to be > estimated. > > Will anyone out there please help me? > Thanks. > Miguel. > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

- Prev by Date:
**st: Solving simultaneous equations** - Next by Date:
**Re: st: Pointer to class member function?** - Previous by thread:
**st: Solving simultaneous equations** - Next by thread:
**st: Standard error of the weighted mean** - Index(es):