search for: meang1sp

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2007 Mar 02
1
Help with faster optimization for large parameter problem
Hello all, I have a large parameter problem with the following very simple likelihood function: fn<-function(param) { x1<-param[1:n] g1<-param[(n+1):(2*n)] beta<-param[(2*n+1):(2*n+k)] sigma2<-param[2*n+k+1]^2 meang1sp<-mean(g1[sp]) mu<-beta%*%matrix(x1,1,n)-(g1[sp]-meang1sp)%*%matrix(g1,1,n) return(sum((ydc-mu)^2)/(2*sigma2) + n*k*log(sqrt(sigma2)) + mean(x1)^2 + mean(g1)^2 + 1000*(x1[1]>x1[n])) } There's nothing special here -- it's just plain old OLS, except all the variables on the r...