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A Bayesian parameter estimation approach is developed for the estimation of joint probability distribution functions for colloid and bacterial fate and transport model parameters describing breakthrough curves (BTCs) obtained through porous media column studies, and is applied to data involving different ionic strength solutions to fit models of differing complexity.
In the literature, hydrological models of differing complexity are proposed for estimating the water resources of semi-arid catchments, and also to evaluate rainfall data sets.
Six biogeochemical models of differing complexity were coupled with a pre-calibrated two-dimensional hydrodynamic model of Cell 4 and tested against field data.
As phenomenological process models, a large number of probabilistic and kinetic approaches of differing complexity are available which mostly provide information on the screening rate or efficiency.
After exploring parameter importance using symbolic regression, we evaluated a set of candidate models of differing complexity according to the number of season-specific parameters.
Various simplifications were necessary to allow rapid calculation of a valid workload measurement across departments, for example grouping together some studies of differing complexity in one RVU category.
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This paper examines the performances of classifiers of differing complexities in relation to the complexity of feature-label distributions in the case of small samples.
In summary, using PhyloSort we were able to rapidly inspect thousands of phylogenetic trees of differing complexities and number of terminal taxa and demonstrate the contribution of cyanobacterial primary EGT to Plantae nuclear genomes.
Bock carried out a series of experiments in healthy adults pairing walking tasks of differing complexities (preferred and fast speeds, straight and circle paths, and obstacle avoidance) with either manual (buttoning, checking boxes on clipboard) or cognitive (spelling, verbal recall of visual objects) tasks [ 50].
Among the SNP genotyping technologies available to date, the GoldenGate assay developed by Illumina has demonstrated high success rates within plant genomes of differing complexities, such as pea [ 11], soybean [ 12], barley [ 13], maize [ 14], spruces [ 15] and pines [ 16- 18].
To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com