187 research outputs found
Further considerations on a new indicator for higher education student performance
No full textIl presente lavoro si inserisce nel dibattito internazionale sul sistema di voto universitario e sulla sua sintesi come misura della performance di uno studente. Partendo dalla nuova misura proposta in Adelfio et al. (2014), in questo breve articolo si pone l’enfasi sull’importanza della scelta della misura opportuna, soprattutto nella individuazione delle possibili determinanti della performance, utile nella scelte delle opportune politiche di intervento sulla performance della carriera dello studente. Per richiamare il nuovo indicatore proposto e per fare il confronto con quello esistente, si `e fatto riferimento ai Sistema Universitario italiano.This paper joins the international debate on academic achievements; in particular, it offers some reflections about the suitable system of marks and their synthesis, since it is usually used as a performance academic student measure. Starting from a new measure proposed by Adelfio et al. (2014), this paper highlights the importance of the measure chosen in studying the determinants of the performance. The Italian University System is used as reference system in order to briefly recall
the need of the new measure and to make comparison between the current indicator and the proposed one on real data. Results highlight the importance of the choice of the proper performance measure, in order to take efficient policies aimed at improving student’s performance
Some properties of local weighted second-order statistics for spatio-temporal point processes
No full textDiagnostics of goodness-of-fit in the theory of point processes are often considered through the transformation of data into residuals as a result of a thinning or a rescaling procedure. We alternatively consider here second-order statistics coming from weighted measures. Motivated by Adelfio and Schoenberg (2009) for the temporal and spatial cases, we consider an extension to the spatio-temporal context in addition to focussing on local characteristics. In particular, our proposed method assesses goodness-of-fit of spatio-temporal models by using local weighted secondorder statistics, computed after weighting the contribution of each observed point by the inverse of the conditional intensity function that identifies the process. Weighted second-order statistics directly apply to data without assuming homogeneity nor transforming the data into residuals, eliminating thus the sampling variability due to the use of a transforming procedure. We provide some characterisations and show a number of simulation studies
Kernel estimation and display of a five-dimensional conditional intensity function
No full textThe aim of this paper is to find a convenient and effective method of displaying some second order properties in a neighbourhood of a selected point of the process. The used techniques are based on very general high-dimensional nonparametric smoothing developed to define a more general version of the conditional intensity function introduced in earlier earthquake studies by Vere-Jones (1978)
University student talent: the real driver for performance?
No full textInvestigation about the university student performance, and its measurement, are
very crucial issues for any policy maker. Since the economic crisis, jobs market requires even
higher skills and competences. Literature offers a lot of papers about the university student
quality and performance, in order to identify the main determinants of them. Often, results are
very different, and they seems to hold just in a specific context. This paper aims to investigate
the role of a latent variable that can take into account the student motivation, aptitude, and
abilities, here conveniently called talent. A random effect Quantile Regression on a new measure
of Italian student performance has been adopted, and results seem to highlight the main role
of the talent
Space-time Point Processes semi-parametric estimation with predictive measure information
No full textIn this paper, we provide a method to estimate the space-time intensity of a branching-type point process by mixing
nonparametric and parametric approaches.
The method accounts simultaneously for the
estimation of the different model components, applying a
forward predictive likelihood estimation approach to
semi-parametric models
A space-time branching process with covariates
No full textThe paper proposes a stochastic process that improves the assessment of seismic events in
space and time, considering a contagion model (branching process) within a regression-like framework.
The proposed approach develops the Forward Likelihood for prediction (FLP) method including
covariates in the epidemic component
Point processes residual analysis and asymptotical distribution of transformed versions of some second-order statistics
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