Jean Marie Linhart

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All mathematical models of real-world phenomena contain parameters that need to be estimated from measurements, either for realistic predictions or simply to understand the characteristics of the model. Bayesian statistics provides a framework for parameter estimation in which uncertainties about models and measurements are translated into uncertainties in(More)
To understand the mechanisms leading to coexistence and exclusion, it is essential to establish information on the nutritional needs of species. We focused on the frequently coexisting Pseudo-nitzschia species, P. delicatissima and P. galaxiae, capable of forming blooms and producing domoic acid. We employed monoculture experiments to determine growth(More)
We present and compare three C functions to compute the logarithm of the cumulative standard normal distribution. The first is a new algorithm derived from Algorithm 304’s calculation of the standard normal distribution via a series or continued fraction approximation, and it is good to the accuracy of the machine. The second is based on Algorithm(More)
We study singularity formation in spherically symmetric solitons of the charge one sector of the (2+1) dimensional S2 sigma model, also known as CP 1 wave maps, in the adiabatic limit. These equations are non-integrable, and so studies are performed numerically on radially symmetric solutions using an iterative finite differencing scheme. Analytic estimates(More)
We study singularity formation in spherically symmetric solitons of the (4+1) dimensional Yang Mills model and the charge two sector of the (2+1) dimensional S2 sigma model, also known as CP 1 wave maps, in the adiabatic limit. These two models are very similar. Studies are performed numerically on radially symmetric solutions using an iterative finite(More)
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