Combined Error Models
Combined Error Models is a statistical modeling framework that integrates both additive and proportional error components to characterize residual unexplained variability in pharmacometric and quantitative systems pharmacology analyses.
35
Publications
1.7K
Citations
96
Authors
49
Institutions
Publications per year
2017–2026
11
Variants
Combined Residual Error Models
35
Error analysis and simulations of complex phenomena
Michael Andrew Christie, James Glimm, John W. Grove et al. · 2005 · 81 citations
Engineering, Computational Engineering, Petroleum Engineering +10
NeSSM: A Next-Generation Sequencing Simulator for Metagenomics
Ben Jia, Liming Xuan, Kaiye Cai et al. · PLoS ONE · 2013 · 77 citations · Full text
Life Sciences, Biology, Microbiology +13
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University of Maryland, College Park, United States
2 publications · 109 citations
2
h-index
1–5 of 96
49
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
4 publications
161 citations
Institute of Geodesy and Geophysics
Wuhan, China
2 h-index
6 publications
116 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
8 publications
178 citations

Kyoto University
Kyoto, Japan
2 h-index
2 publications
48 citations
Los Alamos National Laboratory
Los Alamos, United States
2 h-index
6 publications
2K citations
Charles University
Prague, Czechia
2 h-index
3 publications
63 citations
Wuhan University of Science and Technology
Wuhan, China
2 h-index
2 publications
48 citations
University of Lausanne
Lausanne, Switzerland
2 h-index
4 publications
114 citations
1–8 of 49
2 publications · 109 citations
2
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CAGEO · 1 publications · 22 citations
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Repository · 1 publications · 305 citations
1
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1 publications · 31 citations
1
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1 publications · 29 citations
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