Vimal wrote: > Hi, > > If in EM, I assume that p(x) is a known\complete pdf and q(x) being > the pdf of incomplete data, then > > Can I say that: > 1) For EM, E-step: \int p(x) log(q(x)) dx
No, I think you need tio improve your notation... let p(x,y), q(x,y) be the true and modelled density of joint random variables, where x is observed and y is unobserved .. then the expectation step evaluates E (log(q(y|x))), where the expectation is with respect to the density q(y|x) (ie. the conditional density of y given x). IE. E-step: l*(x)= \int q(y|x)) log(q(y|x)) dy Then the maximisation step is to maximise l*(x) (ie using the sample value of x)... but this is notionally an approximation to the real target of maximising the expectation of l*(x), where the expectation is with respect to the marginal distribution of x. M-step : maximise \int p(x) l*(x) dx. This would probably make more sense if further notation were introduced relating to the parameters being estimated. David Jones . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
