RE: eigenvalues

From: [email protected] [mailto:[email protected]] On Behalf Of Jeroen Elassaiss-Schaap Sent: Friday, November 06, 2015 11:34 To: Pavel Belo Cc: “[email protected]” Subject: Re: [NMusers] eigenvalues Hi Pavel, For starters, it is simple to calculate using R: mymat<-abs(matrix(rnorm(25^2),ncol=25)) mymat <- mymat /max(mymat) #replace mymat with your nonmem $cov matrix eigenval<-eigen(mymat,symm=T)$values # should be similar to nonmem reported cn<-max(eigenval)/min(eigenval) eigenval<-eigen(mymat[1:10,1:10],symm=T)$values cn1<-max(eigenval)/min(eigenval) # could be compared to the "PK" parameters ratio from monolix Assuming a 25x25 covariance matrix, and theta in 1:10. You will need to do some rearrangement of the cells to isolate the off-diagonal elements of $OMEGA, but with this approach you can compare apples by apples. Until you have done that you will not know whether the platforms provide different results or similar wrt the condition number. The difference in behavior with respect to objective function impact is puzzling, assuming you refer to SAEM estimation in Nonmem. My advice here would be to focus on (visual) predictive checks, and compare how well the two platforms perform on that aspect. Hope this helps, Jeroen -- http://pd-value.com [email protected] @PD_value +31 6 23118438 -- More value out of your data!