1,354,434 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
Local indicators of spatio-temporal association on linear networks
No full textIn this work, we extend the Local Indicators of Spatio-Temporal Association (LISTA) functions (Siino et al. 2018) to the non-Euclidean space of linear networks. We introduce the local version of some inhomogeneous second-order statistics for spatio-temporal point processes on linear networks (Morandi and Mateu, 2019), namely the K-function and the pair correlation function.
Following the work of Adelfio et al. (2019) for the Euclidean case, we employ the proposed LISTA functions to assess the goodness-of-fit of different spatio-temporal models fitted to point patterns occurring on linear networks. Indeed, the peculiar lack of homogeneity in a network discourages the usage of traditional spatial and spatio-temporal methods based on stationary processes. Therefore, the weighted second-order statistics are appropriate diagnostic tools since they directly apply to data without assuming homogeneity.
We provide simulation studies, by generating both inhomogeneous and self-exiting spatio-temporal point processes on networks, and by carrying out diagnostics on different fitted intensities. By comparing the values of the LISTA functions and their theoretical values, we show that the LISTA can correctly identify the true intensity when this is constrained on a network
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)
Weighted local second-order statistics for complex spatio-temporal point processes
No full textSpatial, temporal, and spatio-temporal point processes, and in particular Poisson processes, are stochastic processes that are largely used to describe and model the distribution of a wealth of real phenomena.
When a model is fitted to a set of random points, observed in a given multidimensional space, diagnostic measures are necessary to assess the goodness-of-fit and to evaluate the ability of that model to describe the random point pattern behaviour. The main problem when dealing with residual analysis for point processes is to find a correct definition of residuals. Diagnostics 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 (2010) for the spatial case, we consider here an extension to the spatio-temporal context in addition to focussing on local characteristics.
Then, rather than using global characteristics, we introduce local tools, considering individual contributions of a global estimator as a measure of clustering. Generally, the individual contributions to a global statistic can be used to identify outlying components measuring the influence of each contribution to the global statistic.
In particular, our proposed method assesses goodness-of-fit of spatio-temporal models by using local weighted second-order 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
An analysis of earthquakes clustering based on a second-order diagnostic approach
No full textA diagnostic method for space–time point process is here introduced and applied to seismic data of a fixed area of Japan. Nonparametric methods are used to estimate the intensity function of a particular space–time point process and on the basis of the proposed diagnostic method, second-order features of data are analyzed: this approach seems to be useful to interpret space–time variations of the observed seismic activity and to focus on its clustering features
Probabilistic forecast for Northern New Zealand seismic process: a kernel-based approach
No full textForecast of earthquakes of a given area of Northern New Zealand is provided.
It is based on the assumption that future earthquakes activity may be based
on the smoothing of past earthquakes. Therefore, seismic activity is described by an
intensity function factorized into kernel functions which depend on time longitude
and latitude of events
A new approach for clustering of effects in quantile regression
No full textIn this paper we aim at nding similarities among the coefficients from a multivariate regression. Using a quantile regression coefficients modeling, the effect of each covariate, given a response (also multivariate) is a curve in the multidimensional space of the percentiles. Collecting all the curves, describing the effects of each covariate on each response variable, we could be able to assess if only one or more covariates have same effects on different responses
Financial contagion through space-time point processes
No full textWe propose to study the dynamics of financial contagion by means of a class of
point process models employed in the modeling of seismic contagion. The proposal
extends network models, recently introduced to model financial contagion, in a
space-time point process perspective. The extension helps to improve the assessment of credit risk of an institution, taking into account contagion spillover effects
- …
