Two general methods for population pharmacokinetic modeling: Non-parametric adaptive grid and non-parametric Bayesian

Journal of Pharmacokinetics and Pharmacodynamics

Volumn 40, Issue 2, 2013, Pages 189-199

  Tatarinova, Tatiana ^a   Neely, Michael ^a   Bartroff, Jay ^a,b   Van Guilder, Michael ^a   Yamada, Walter ^a,d   Bayard, David ^a,c   Jelliffe, Roger ^a   Leary, Robert ^a,e   Chubatiuk, Alyona ^b   Schumitzky, Alan ^a,b  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^c CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^d AZUSA PACIFIC UNIVERSITY   (United States)

^e PHARSIGHT CORPORATION   (United States)

Author keywords

Bayesian; Maximum likelihood; Non parametric; Pmetrics; Population pharmacokinetic modeling; RJags; Stick breaking

Indexed keywords

ALGORITHM; ARTICLE; BAYES THEOREM; CALCULATION; INTERMETHOD COMPARISON; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MAXIMUM LIKELIHOOD METHOD; NONPARAMETRIC ADAPTIVE GRID MODEL; NONPARAMETRIC BAYESIAN MODEL; PHARMACOKINETICS; POPULATION DISTRIBUTION; PRIORITY JOURNAL; PROCESS MODEL; PROCESS OPTIMIZATION; SIMULATION;

ALGORITHMS; BAYES THEOREM; COMPUTER SIMULATION; HUMANS; MODELS, BIOLOGICAL;

EID: 84880698337     PISSN: 1567567X     EISSN: 15738744     Source Type: Journal    
DOI: 10.1007/s10928-013-9302-8     Document Type: Article

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