No abstract

Mathematical simulation models are commonly applied to analyze experimental or environmental data and eventually to acquire predictive capabilities. Typically these models depend on poorly defined, unmeasurable parameters that need to be given a value. Fitting a model to data, so-called inverse modelling, is often the sole way of finding reasonable values for these parameters. There are many challenges involved in inverse model applications, e.g., the existence of non-identifiable parameters, the estimation of parameter uncertainties and the quantification of the implications of these uncertainties on model predictions. The R package FME is a modeling package designed to confront a mathematical model with data. It includes algorithms for sensitivity and Monte Carlo analysis, parameter identifiability, model fitting and provides a Markov-chain based method to estimate parameter confidence intervals. Although its main focus is on mathematical systems that consist of differential equations, FME can deal with other types of models. In this paper, FME is applied to a model describing the dynamics of the HIV virus.

No abstract

The rate and factors controlling denitrification in marine sediments have been investigated using a prognostic diagenetic model. The model is forced with observed carbon fluxes, bioturbation and sedimentation rates, and bottom water conditions. It can reproduce rates of aerobic mineralization, denitrification, and fluxes of oxygen, nitrate, and ammonium. The globally integrated rate of denitrification is estimated by this model to be about 230–285 Tg N yr−1, with about 100 Tg N yr−1 occurring in shelf sediments. This estimate is significantly higher than literature estimates (12–89 Tg N yr−1), mainly because of a proposed upward revision of denitrification rates in slope and deep‐sea sediments. Higher sedimentary denitrification estimates require a revision of the marine nitrogen budget and lowering of the oceanic residence time of nitrogen down to about 2×103 years and are consistent with reported low N/P remineralization ratios between 1000 and 3000 m. Rates of benthic denitrification are most sensitive to the flux of labile organic carbon arriving at the sediment‐water interface and bottom water concentrations of nitrate and oxygen. Denitrification always increases when bottom water nitrate increases but may increase or decrease if oxygen in the bottom water increases. Nitrification is by far the most important source of nitrate for denitrification, except for organic‐rich sediments underlying oxygen‐poor and nitrate‐rich water.

Although R is still predominantly applied for statistical analysis and graphical representation, it is rapidly becoming more suitable for mathematical computing. One of the fields where considerable progress has been made recently is the solution of differential equations. Here we give a brief overview of differential equations that can now be solved by R.

No abstract

Although R is still predominantly applied for statistical analysis and graphical representation, it is rapidly becoming more suitable for mathematical computing. One of the fields where considerable progress has been made recently is the solution of differential equations. Here we give a brief overview of differential equations that can now be solved by R.

No abstract