R-based reproduction of the estimation process hidden behind NONMEM® Part 2: First-order conditional estimation | Zendy

KyunSeop Bae | Zendy; DongSeok Yim | Zendy

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R-based reproduction of the estimation process hidden behind NONMEM® Part 2: First-order conditional estimation

Author(s) -

KyunSeop Bae,

DongSeok Yim

Publication year - 2016

Publication title -

translational and clinical pharmacology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.166

H-Index - 6

eISSN - 2383-5427

pISSN - 2289-0882

DOI - 10.12793/tcp.2016.24.4.161

Subject(s) - estimation , reproduction , statistics , nonmem , process (computing) , computer science , mathematics , population , biology , engineering , demography , sociology , ecology , systems engineering , operating system

The first-order conditional estimation (FOCE) method is more complex than the first-order (FO) approximation method because it estimates the empirical Bayes estimate (EBE) for each iteration. By contrast, it is a further approximation of the Laplacian (LAPL) method, which uses secondorder expansion terms. FOCE without INTERACTION can only be used for an additive error model, while FOCE with INTERACTION (FOCEI) can be used for any error model. The formula for FOCE without INTERACTION can be derived directly from the extension of the FO method, while the FOCE with INTERACTION method is a slight simplification of the LAPL method. Detailed formulas and R scripts are presented here for the reproduction of objective function values by NONMEM.

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