H. T. Banks, J. E. Banks, K. Link, J. A. Rosenheim, C. Ross et al., Model comparison tests to determine data information content, CRSC-TR14-13, Applied Mathematics Letters, pp.43-53, 2014.
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H. T. Banks, J. E. Banks, N. Murad, J. Rosenheim, and K. Tillman, Modelling Pesticide Treatment Effects on Lygus hesperus in Cotton Fields, 2015.
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URL : https://hal.archives-ouvertes.fr/hal-01626902

H. T. Banks, J. E. Banks, J. Rosenheim, and K. Tillman, Modeling populations of Lygus Hesperus on cotton fields in the San Joaquin Valley of California: The importance of statistical and mathematical model choice, J. Biological Dynamics, 2015.

H. T. Banks, M. Doumic, C. Kruse, S. Prigent, and H. Rezaei, Information content in data sets for a nucleated-polymerization model, CRSC- TR14-15, J. Biological Dynamics, 2014.

H. T. Banks and B. G. Fitzpatrick, Statistical methods for model comparison in parameter estimation problems for distributed systems, Journal of Mathematical Biology, vol.15, issue.5, pp.28-501, 1990.
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H. T. Banks, J. Catenacci, and S. Hu, Applications of difference-based variance estimation methods, CRSC-TR15-05, pp.sub- mitted, 2015.

H. T. Banks, S. Hu, and W. C. Thompson, Modeling and Inverse Problems in the Presence of Uncertainty, 2014.
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H. T. Banks and H. T. Tran, Mathematical and Experimental Modeling of Physical and Biological Processes, 2009.

H. T. Banks, Z. R. Kenz, and W. C. Thompson, An extension of RSS-based model comparison tests for weighted least squares, Intl. J. Pure and Appl. Math, pp.79-155, 2012.
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M. Brabec, A. Hon?k, S. Pekár, and Z. Martinková, Population Dynamics of Aphids on Cereals: Digging in the Time-Series Data to Reveal Population Regulation Caused by Temperature, PLoS ONE, vol.181, issue.9, p.106228, 2014.
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J. D. Brawn, S. K. Robinson, and F. R. Thompson, The Role of Disturbance in the Ecology and Conservation of Birds, Annual Review of Ecology and Systematics, vol.32, issue.1, pp.32-251, 2001.
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K. P. Burnham and D. R. Anderson, Multimodel Inference, Sociological Methods & Research, vol.27, issue.1, pp.261-304, 2004.
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M. Davidian and D. M. Giltinan, Nonlinear Models for Repeated Measurement Data, 2000.

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V. E. Forbes, P. Calow, V. Grimm, T. Hayashi, T. Jager et al., Integrating population modeling into ecological risk assessment, Integrated Environmental Assessment and Management, vol.16, issue.1, pp.191-193, 2010.
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H. Motulsky and A. Christopoulos, Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting, 2004.

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J. A. Rosenheim, K. Steinmann, G. A. Langelloto, and A. G. Link, Estimating the Impact of <I>Lygus hesperus</I> on Cotton: The Insect, Plant, and Human Observer as Sources of Variability, Environmental Entomology, vol.35, issue.5, pp.35-1141, 2006.
DOI : 10.1603/0046-225X(2006)35[1141:ETIOLH]2.0.CO;2

M. H. Schultz, Spline Analysis, 1973.

J. D. Stark, J. E. Banks, and R. I. Vargas, How risky is risk assessment? The role that life history strategies play in susceptibility of species to pesticides and other toxicants, Proc. Nat. Acad. Sci, pp.732-736, 2004.

J. D. Stark, R. Vargas, and J. E. Banks, Incorporating Ecologically Relevant Measures of Pesticide Effect for Estimating the Compatibility of Pesticides and Biocontrol Agents, Journal of Economic Entomology, vol.100, issue.4, pp.1027-1032, 2007.
DOI : 10.1093/jee/100.4.1027

J. D. Stark, R. Vargas, and J. E. Banks, Incorporating variability in point estimates in risk assessment: Bridging the gap between LC50 and population endpoints, Environmental Toxicology and Chemistry, vol.37, issue.7, pp.34-1683, 2015.
DOI : 10.1006/eesa.1997.1552