0000000001301115
AUTHOR
Rafael Romero
sj-pdf-1-smr-10.1177_00491241221092725 - Supplemental material for Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for Ecological Inference Based on Linear Programming
Supplemental material, sj-pdf-1-smr-10.1177_00491241221092725 for Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for Ecological Inference Based on Linear Programming by Jose M. Pavía and Rafael Romero in Sociological Methods & Research
IDCnet: Inclusive Design Curriculum Network – First Results
This paper presents the preliminary results of the IDCnet Thematic Network in regard to the development of curriculum recommendations for Higher Education institutions in the area of ICT that include Design for All. These recommendations are based upon discussion with relevant actors in industry and academia to identify core knowledge sets and skills.
sj-pdf-1-smr-10.1177_00491241221092725 - Supplemental material for Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for Ecological Inference Based on Linear Programming
Supplemental material, sj-pdf-1-smr-10.1177_00491241221092725 for Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for Ecological Inference Based on Linear Programming by Jose M. Pavía and Rafael Romero in Sociological Methods & Research
Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election
[EN] Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. Compared to other linear and quadratic programming models previously published, our approach presents two important innovations. Firstly, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote behaviour of young electors voting for the first time. Secondly, by exploiting the information contained in the model…
Intracranial measurement of current densities induced by transcranial magnetic stimulation in the human brain
Transcranial magnetic stimulation (TMS) is a non-invasive technique that uses the principle of electromagnetic induction to generate currents in the brain via pulsed magnetic fields. The magnitude of such induced currents is unknown. In this study we measured the TMS induced current densities in a patient with implanted depth electrodes for epilepsy monitoring. A maximum current density of 12 microA/cm2 was recorded at a depth of 1 cm from scalp surface with the optimum stimulation orientation used in the experiment and an intensity of 7% of the maximal stimulator output. During TMS we recorded relative current variations under different stimulating coil orientations and at different points…
Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for Ecological Inference Based on Linear Programming
The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find solutions stemming from the former, with the latter being less active. From the mathematical programming framework, this paper suggests a new direction for tackling this problem. For the first time in the literature, a procedure based on linear programming is proposed to attain estimates of local contingency tables. Based on this and the homogeneity hypot…
Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election
Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. Compared to other linear and quadratic programming models previously published, our approach presents two important innovations. Firstly, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote behaviour of young electors voting for the first time. Secondly, by exploiting the information contained in the model resi…