A primer on model selection using the Akaike Information Criterion
Tài liệu tham khảo
Akaike, 1973, Information theory and an extension of the maximum likelihood principle, 267
Akaike, 1974, A new look at the statistical model identification, IEEE Transactions on Automatic Control, 19, 716, 10.1109/TAC.1974.1100705
Baker, 2005, Computational modelling with functional differential equations: Identification, selection, and sensitivity, Applied Numerical Mathematics, 53, 107, 10.1016/j.apnum.2004.08.014
Burnham, 2002
Casement, 1984
Coelho, 2011, A Bayesian framework for parameter estimation in dynamical models, PLoS One, 6, 1, 10.1371/journal.pone.0019616
Colakoglu, 2009, Intermediate filaments exchange subunits along their length and elongate by end-to-end annealing, Journal of Cell Biology, 185, 769, 10.1083/jcb.200809166
Friston, 2002, Bayesian estimation of dynamical systems: An application to fMRI, NeuroImage, 16, 513, 10.1006/nimg.2001.1044
Gotoh, 2016, Model-driven experimental approach reveals the complex regulatory distribution of p53 by the circadian factor period 2
Hurvich, 1989, Regression and time series model selection in small samples, Biometrika, 76, 297, 10.1093/biomet/76.2.297
Jacquier, 2018, Investigation of novel regulation of n-myristoyltransferase by mammalian target of rapamycin in breast cancer cells, Scientific Reports, 8, 10.1038/s41598-018-30447-0
Janzén, 2016, Parameter identifiability of fundamental pharmacodynamic models, Frontiers in Physiology, 7, 590, 10.3389/fphys.2016.00590
Johnson, 2004, Model selection in ecology and evolution, Trends in Ecology & Evolution, 19, 101, 10.1016/j.tree.2003.10.013
Kirmse, 2007, A quantitative kinetic model for the in vitro assembly of intermediate filaments from tetrameric vimentin, Journal of Biological Chemistry, 282, 18563, 10.1074/jbc.M701063200
Kullback, 1951, On information and sufficiency, The Annals of Mathematical Statistics, 22, 79, 10.1214/aoms/1177729694
Miao, 2009, Differential equation modeling of HIV viral fitness experiments: Model identification, model selection, and multimodel inference, Biometrics, 65, 292, 10.1111/j.1541-0420.2008.01059.x
Pitt, 2019, Parameter estimation in models of biological oscillators: An automated regularised estimation approach, BMC Bioinformatics, 20, 82, 10.1186/s12859-019-2630-y
Portet, 2015, Studying the cytoskeleton: Case of intermediate filaments, Insights, 8, 1
Portet, 2015, Keratin dynamics: Modeling the interplay between turnover and transport, PLoS One, 10, 10.1371/journal.pone.0121090
Sagar, 2018, Dynamic optimization with particle swarms (DOPS): A meta-heuristic for parameter estimation in biochemical models, BMC Systems Biology, 12, 87, 10.1186/s12918-018-0610-x
Sugiura, 1978, Further analysis of the data by Akaike’s Information Criterion and the finite corrections, Communications in Statistics - Theory and Methods, 7
Symonds, 2011, A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion, Behavioral Ecology and Sociobiology, 65, 13, 10.1007/s00265-010-1037-6
Winheim, 2011, Deconstructing the late phase of vimentin assembly by total internal reflection fluorescence microscopy (TIRFM), PLoS One, 6, 10.1371/journal.pone.0019202
Yates, 2006, Structural identifiability of physiologically based pharmacokinetic models, Journal of Pharmacokinetics and Pharmacodynamics, 33, 421, 10.1007/s10928-006-9011-7
Zhang, 2015, On the selection of ordinary differential equation models with application to predator-prey dynamical models, Biometrics, 71, 131, 10.1111/biom.12243
