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From |
marcel spijkerman <marcel_spijkerman@hotmail.com> |

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

Subject |
RE: st: predictions from ML program |

Date |
Mon, 9 Jun 2008 12:26:39 +0000 |

Thanks Maarten for your suggestions. Let me explain what I mean by 'efficiently'; I am a GAUSS user but now I am 'forced' to use STATA. For example; to calculate the quantity b'X where b' is a vector of estimated parameters, I do know how to call these parameters (e(b)) but to compute b'X I do not know other than: b0 + b1*x1 + b2*x2 ........ So every time I change the specification I have to adjust these lines. It would be handy to know of some procedure that automates this to some extent and I do not know where to look in Stata (I tried something with 'foreach'????). Regards, Marcel > Date: Fri, 6 Jun 2008 12:38:38 +0100 > From: maartenbuis@yahoo.co.uk > Subject: Re: st: predictions from ML program > To: statalist@hsphsun2.harvard.edu > > --- marcel spijkerman wrote: >> I am estimating by ML a likelihood of the form: >> >> L = ln(p1*L1 + p2*L2 + p3*L3 + p4*L4) >> >> where the p's are mixture probabilities and the L's are likelihood >> contributions of a survival density. now I want to estimate the >> parameters of this likelihood by the EM - algorithm, and therefore I >> need to compute the likelihood contribution for each individual and >> each term given de data and current parameter estimates. My question >> is how I can do this effeciently, thus given e(b) from a previous >> step, computing the likelihood contributions for each term, use these >> to upfdate the p's and estimate the parameters again? > > There is no nicely packaged suite of commands that will help you do a > EM, so you'll have to do it yourself. Given that, your first concern > should be to get it working correctly. Once you've done that you can > start worrying about efficiency. Basically you'll want a -while- loop. > Call the parameters of L1, L2, etc, b, than below will give you a rough > sketch of such a program. > > Hope this helps, > Maarten > > *----------------- begin sketch ----------------- > local `i' = 1 > while `critll'> `emltolerance' & /// > `critb'> `emtolerance' & /// > `i' < `emiterate'{ > > scalar `old_ll' = r(new_ll) > matrix `old_b' = r(init) > Ls `varlist' `wgt' if `touse', other options > Ps `varlist' `wgt' if `touse', other options > scalar `critll' = reldif(r(new_ll),`old_ll') > scalar `critb' = mreldif(r(init),`old_b') > local ++i > } > > program define Ps, rclass > maximize likelihood with respect to b, while fixing p > end > > program define Ps, rclass > maximize likelihood with respect to p1, p2, etc while fixing bs > end > *----------------- end sketch ----------------- > > ----------------------------------------- > Maarten L. Buis > Department of Social Research Methodology > Vrije Universiteit Amsterdam > Boelelaan 1081 > 1081 HV Amsterdam > The Netherlands > > visiting address: > Buitenveldertselaan 3 (Metropolitan), room Z434 > > +31 20 5986715 > > http://home.fsw.vu.nl/m.buis/ > ----------------------------------------- > > > __________________________________________________________ > Sent from Yahoo! Mail. > A Smarter Email http://uk.docs.yahoo.com/nowyoucan.html > * > * 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/ _________________________________________________________________ Express yourself instantly with MSN Messenger! Download today it's FREE! http://messenger.msn.click-url.com/go/onm00200471ave/direct/01/ * * 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/

**References**:**st: predictions from ML program***From:*marcel spijkerman <marcel_spijkerman@hotmail.com>

**Re: st: predictions from ML program***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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