Different OFV in Pumas compared to NONMEM

Hi, I was wondering if Pumas and NONMEM calculate OFV in different ways? A model I converted from NONMEM to pumas is identical in every way besides the OFV

hi Pawan -

Welcome to the community!

Pumas reports the loglikelihood whereas NONMEM reports the -2 x loglikelihood.

In Pumas you can do metrics_table(model_fit) where you get a table of metrics which should contain the -2LL that you can compare with NONMEM.

Hope this helps


NONMEM also leaves out the normalization constant of the Gaussian likelihood in their OFV so the exact relationship between the two is

NONMEM_OFV = -2*loglikelihood(_fitted_model) - Pumas.nobs(_fitted_model)*log(2π)

Notice that this only holds true for purely Gaussian models and not, e.g. truncated (M2) or censored (M3) models.

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Thank you, @andreasnoack and @vijay. Using the above relationship, I am able to get the same NONMEM OFV .