Search results for " identifiability"
showing 5 items of 5 documents
Compartmental analysis of dynamic nuclear medicine data: Models and identifiability
2016
Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolism in the biological tissue. This paper is the first of a series of two that deal with the problem of tracer coefficient estimation via compartmental modelling in an inverse problem framework. Specifically, here we discuss the identifiability problem for a general n-dimension compartmental system and provide uniqueness results in the case of two-compartment and three-compartment compartmental models. The second paper will utilize this framework in order to show how non-linear regularization schemes can be applied t…
Identifiability problem for recovering the mortality rate in an age-structured population dynamics model
2014
In this article is studied the identifiability of the age-dependent mortality rate of the Von Foerster–Mc Kendrick model, from the observation of a given age group of the population. In the case where there is no renewal for the population, translated by an additional homogeneous boundary condition to the Von Foerster equation, we give a necessary and sufficient condition on the initial density that ensures the mortality rate identifiability. In the inhomogeneous case, modelled by a non-local boundary condition, we make explicit a sufficient condition for the identifiability property, and give a condition for which the identifiability problem is ill-posed. We illustrate this latter case wit…
Identifying Causal Effects with the R Package causaleffect
2017
Do-calculus is concerned with estimating the interventional distribution of an action from the observed joint probability distribution of the variables in a given causal structure. All identifiable causal effects can be derived using the rules of do-calculus, but the rules themselves do not give any direct indication whether the effect in question is identifiable or not. Shpitser and Pearl constructed an algorithm for identifying joint interventional distributions in causal models, which contain unobserved variables and induce directed acyclic graphs. This algorithm can be seen as a repeated application of the rules of do-calculus and known properties of probabilities, and it ultimately eit…
Identifiability analysis for pressure sensors positioning
2017
The identifiability analysis is investigated as sampling design method aimed to the leakage detection in looped water distribution networks. The preliminary ranking of the candidate nodes for the pressure sensors positioning is performed by running several hydraulic simulations and calculating sensitivity functions. The reduced subset of nodes and their sensitivities are then used to perform the identifiability analysis by calculating the collinearity index which provides the maximum number of sensors and their location into the network. The index selects the nodes according to their sensitivities to several leakages scenarios, simulated in EPANET by changing the emitter coefficient of the …
A comprehensive analysis for N2O mechanisms by advanced mathematical techniques
2018
Recent evaluation of the existing activated sludge models, incorporating nitrous oxide (N2O) formation, is only based on the capabilities and inabilities in describing experimental data under different conditions. This paper will present an advanced mathematical modeling framework (i.e. coupling global sensitivity, identifiability and uncertainty analysis) for a comprehensive analysis on the evaluation of the structural differences among three ammonia oxidizing bacteria (AOB) two-pathway models in combination with two heterotrophic denitrification models. The analysis will be performed based on experimental data from a lab-scale deammonification granular sequencing batch reactor operated un…