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From |
Denis Kalugin <denis.kalugin@gmail.com> |

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

Subject |
st: NLLS w/ normal distribution - some parameters not estimated |

Date |
Sun, 13 Jun 2010 15:19:34 +0400 |

Dear All, I'm trying to do a non-linear least squares estimation to nail down a latent dependence. The latent variables can be regressed on a linear form and look like L1=xb1+error1 L2=xb2+error2 The probabilities of observing a value of y is given by P(y=-1)=P(L1<z)=norm( (z-xb1)/error1 ), P(y=1)=P(z<min(L1,L2))=( 1- norm( (z-xb1)/error1 ) )*( 1- norm( (z-xb2)/error2 ) ) P(y=0) = 1 - P(y=1) - P(y=-1) The expected value of the observable dependent variable is given by P(y1=1| b1,b2) - P(y1=-1| b1,b2) so the expected value becomes E(y_i)=( 1- normal ( (z-xb1)/error1) )*( 1- normal ( (z-xb2)/error2) ) - normal ( (z-xb1)/error1) ). The problem is that when I estimate this equation, all the b1 parameters are not estimates, and are reported as if they were constants. How can i address this problem? Furthermore, I don't know how to include individual error terms in the regression. Including them as parameters does not do the trick, they need to be drawn from the original L1 and L2 equations somehow. Is there a way to do this? Thanks in advance! Best regards, Denis. * * 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/

**Follow-Ups**:**Re: st: NLLS w/ normal distribution - some parameters not estimated***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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