0000000000148046
AUTHOR
Francisco-j. Santonja
showing 5 related works from this author
A probabilistic estimation and prediction technique for dynamic continuous social science models: The evolution of the attitude of the Basque Country…
2015
In this paper, a computational technique to deal with uncertainty in dynamic continuous models in Social Sciences is presented.Considering data from surveys,the method consists of determining the probability distribution of the survey output and this allows to sample data and fit the model to the sampled data using a goodness-of-fit criterion based the χ2-test. Taking the fitted parameters that were not rejected by the χ2-test, substituting them into the model and computing their outputs, 95% confidence intervals in each time instant capturing the uncertainty of the survey data (probabilistic estimation) is built. Using the same set of obtained model parameters, a prediction over …
Constructing adaptive generalized polynomial chaos method to measure the uncertainty in continuous models: A computational approach
2015
Due to errors in measurements and inherent variability in the quantities of interest, models based on random differential equations give more realistic results than their deterministic counterpart. The generalized polynomial chaos (gPC) is a powerful technique used to approximate the solution of these equations when the random inputs follow standard probability distributions. But in many cases these random inputs do not have a standard probability distribution. In this paper, we present a step-by-step constructive methodology to implement directly a useful version of adaptive gPC for arbitrary distributions, extending the applicability of the gPC. The paper mainly focuses on the computation…
Solving continuous models with dependent uncertainty: a computational approach
2013
This paper presents a computational study on a quasi-Galerkin projection-based method to deal with a class of systems of random ordinary differential equations (r.o.d.e.'s) which is assumed to depend on a finite number of random variables (r.v.'s). This class of systems of r.o.d.e.'s appears in different areas, particularly in epidemiology modelling. In contrast with the other available Galerkin-based techniques, such as the generalized Polynomial Chaos, the proposed method expands the solution directly in terms of the random inputs rather than auxiliary r.v.'s. Theoretically, Galerkin projection-based methods take advantage of orthogonality with the aim of simplifying the involved computat…
Solving a model for the evolution of smoking habit in Spain with homotopy analysis method
2013
We obtain an approximated analytical solution for a dynamic model for the prevalence of the smoking habit in a constant population but with equal and different from zero birth and death rates. This model has been successfully used to explain the evolution of the smoking habit in Spain. By means of the Homotopy Analysis Method, we obtain an analytic expression in powers of time t which reproduces the correct solution for a certain range of time. To enlarge the domain of convergence we have applied the so-called optimal convergence-control parameter technique and the homotopy-Padé technique. We present and discuss graphical results for our solutions. ©
epiModel: A system to build automatically systems of differential equations of compartmental type-epidemiological models
2011
In this paper we describe epiModel, a code developed in Mathematica that facilitates the building of systems of differential equations corresponding to type-epidemiological linear or quadratic models whose characteristics are defined in text files following an easy syntax. It includes the possibility of obtaining the equations of models involving age and/or sex groups. © 2011.