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In this paper, an optimized fractional order conditional integrator (OFOCI) is proposed.
The clearance (CL) related parameters were estimated with sufficient accuracy in all study designs and all analysis algorithms: the first order (FO), first order conditional estimation (FOCE) and first order conditional estimation with interaction (FOCE-INTER) methods.
NONMEM's first order conditional estimation method was used.
NONMEM's first order conditional estimation method with interaction was used for model development.
The first order conditional estimation with interaction algorithm was used for parameter estimation.
Moreover, a first order conditional independence metric [ 4] has been proposed to specifically detect direct interactions.
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All expressions are presented in terms of the first- and second-order conditional moments.
Results obtained using a first-order conditional moment closure (CMC) approach to modeling turbulent, nonpremixed flames of methane are presented.
Estimating genomic coexpression networks using first-order conditional independence.
This framework exploits first-order conditional independence relationships among gene-expression measurements to estimate patterns of association.
The subroutine ADVAN 9 and first-order conditional estimation with interaction were used throughout the modeling procedure.
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