I was trying to reproduce a result in a published journal, and I have come across some difficulties. I have the following equation, which is two equations combined together. http://r.789695.n4.nabble.com/file/n3006584/Screenshot.png where http://r.789695.n4.nabble.com/file/n3006584/Screenshot-1.png http://r.789695.n4.nabble.com/file/n3006584/Screenshot-2.png http://r.789695.n4.nabble.com/file/n3006584/Screenshot-3.png I[t] is unknown, but have the following distribution http://r.789695.n4.nabble.com/file/n3006584/Screenshot-4.png hence, the probability density function is http://r.789695.n4.nabble.com/file/n3006584/Screenshot-5.png and the likelihood function is http://r.789695.n4.nabble.com/file/n3006584/Screenshot-6.png It used Kiefer's E-M algorithm to estimate the problem. To simplify, first assume lamda is known. I multiply the matrix in the probability density function, and write it in a non-matrix form, and use the function optim() to estimate the maximum. but I got non-sensible estimates of the parameters, and got 39 warnings. the inverse of sigma is negative, and the warnings says that in log(det(sigma)): NaNs produced. What did I do wrong? Can anybody give me a hint? -- View this message in context: http://r.789695.n4.nabble.com/Help-Maximum-likelihood-estimation-tp3006584p3006584.html Sent from the R help mailing list archive at Nabble.com.
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