154 related articles for article (PubMed ID: 19165773)
1. A kernel-based method to determine optimal sampling times for the simultaneous estimation of the parameters of rival mathematical models.
Donckels BM; De Pauw DJ; Vanrolleghem PA; De Baets B
J Comput Chem; 2009 Oct; 30(13):2064-77. PubMed ID: 19165773
[TBL] [Abstract][Full Text] [Related]
2. Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.
Van Derlinden E; Bernaerts K; Van Impe JF
J Theor Biol; 2010 May; 264(2):347-55. PubMed ID: 20064532
[TBL] [Abstract][Full Text] [Related]
3. Optimal experiment design for cardinal values estimation: guidelines for data collection.
Bernaerts K; Gysemans KP; Nhan Minh T; Van Impe JF
Int J Food Microbiol; 2005 Apr; 100(1-3):153-65. PubMed ID: 15854701
[TBL] [Abstract][Full Text] [Related]
4. Accurate estimation of cardinal growth temperatures of Escherichia coli from optimal dynamic experiments.
Van Derlinden E; Bernaerts K; Van Impe JF
Int J Food Microbiol; 2008 Nov; 128(1):89-100. PubMed ID: 18835500
[TBL] [Abstract][Full Text] [Related]
5. Practical application of dynamic temperature profiles to estimate the parameters of the square root model.
Grijspeerdt K; De Reu K
Int J Food Microbiol; 2005 May; 101(1):83-92. PubMed ID: 15878409
[TBL] [Abstract][Full Text] [Related]
6. Experimental design for parameter estimation through sensitivity analysis.
Schlosser PM
J Toxicol Environ Health; 1994 Dec; 43(4):495-530. PubMed ID: 7990173
[TBL] [Abstract][Full Text] [Related]
7. A global parallel model based design of experiments method to minimize model output uncertainty.
Bazil JN; Buzzard GT; Rundell AE
Bull Math Biol; 2012 Mar; 74(3):688-716. PubMed ID: 21989566
[TBL] [Abstract][Full Text] [Related]
8. Optimal experimental design with the sigma point method.
Schenkendorf R; Kremling A; Mangold M
IET Syst Biol; 2009 Jan; 3(1):10-23. PubMed ID: 19154081
[TBL] [Abstract][Full Text] [Related]
9. Robust and efficient design of experiments for the Monod model.
Dette H; Melas VB; Pepelyshev A; Strigul N
J Theor Biol; 2005 Jun; 234(4):537-50. PubMed ID: 15808874
[TBL] [Abstract][Full Text] [Related]
10. Application of global sensitivity analysis to determine goals for design of experiments: an example study on antibody-producing cell cultures.
Kontoravdi C; Asprey SP; Pistikopoulos EN; Mantalaris A
Biotechnol Prog; 2005; 21(4):1128-35. PubMed ID: 16080692
[TBL] [Abstract][Full Text] [Related]
11. Curvature-adjusted optimal design of sampling times for the inference of pharmacokinetic compartment models.
Daimon T; Goto M
Stat Med; 2007 Jun; 26(14):2799-812. PubMed ID: 17072822
[TBL] [Abstract][Full Text] [Related]
12. Reliability of parameter estimation in respirometric models.
Checchi N; Marsili-Libelli S
Water Res; 2005 Sep; 39(15):3686-96. PubMed ID: 16083937
[TBL] [Abstract][Full Text] [Related]
13. Optimal design and mathematical model applied to establish bioassay programs.
Sánchez G; Rodríguez-Díaz JM
Radiat Prot Dosimetry; 2007; 123(4):457-63. PubMed ID: 17182607
[TBL] [Abstract][Full Text] [Related]
14. Practical identifiability of model parameters by combined respirometric-titrimetric measurements.
Petersen B; Gernaey K; Vanrolleghem PA
Water Sci Technol; 2001; 43(7):347-55. PubMed ID: 11385867
[TBL] [Abstract][Full Text] [Related]
15. Bayesian methodology for model uncertainty using model performance data.
Droguett EL; Mosleh A
Risk Anal; 2008 Oct; 28(5):1457-76. PubMed ID: 18793282
[TBL] [Abstract][Full Text] [Related]
16. Sensitivity analysis of uncertainty in model prediction.
Russi T; Packard A; Feeley R; Frenklach M
J Phys Chem A; 2008 Mar; 112(12):2579-88. PubMed ID: 18303866
[TBL] [Abstract][Full Text] [Related]
17. Parametric modeling of DSC-MRI data with stochastic filtration and optimal input design versus non-parametric modeling.
Kalicka R; Pietrenko-Dabrowska A
Ann Biomed Eng; 2007 Mar; 35(3):453-64. PubMed ID: 17160466
[TBL] [Abstract][Full Text] [Related]
18. Evaluation of a minimal experimental design for determination of enzyme kinetic parameters and inhibition mechanism.
Kakkar T; Pak Y; Mayersohn M
J Pharmacol Exp Ther; 2000 Jun; 293(3):861-9. PubMed ID: 10869386
[TBL] [Abstract][Full Text] [Related]
19. Comparison of adaptive psychometric procedures motivated by the theory of optimal experiments: simulated and experimental results.
Remus JJ; Collins LM
J Acoust Soc Am; 2008 Jan; 123(1):315-26. PubMed ID: 18177161
[TBL] [Abstract][Full Text] [Related]
20. Using semivariogram parameter uncertainty in hydrogeological applications.
Pardo-Igúzquiza E; Chica-Olmo M; Garcia-Soldado MJ; Luque-Espinar JA
Ground Water; 2009; 47(1):25-34. PubMed ID: 18793202
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]