0000000001226187
AUTHOR
Salvatore Ingrassia
showing 3 related works from this author
The effect of ISM absorption on stellar activity measurements and its relevance for exoplanet studies
2017
Past UV and optical observations of stars hosting hot Jupiters have shown that some of these stars present an anomalously low chromospheric activity, significantly below the basal level. For WASP-13, observations have shown that the apparent lack of activity is possibly caused by absorption from the intervening ISM. Inspired by this result, we study the effect of ISM absorption on activity measurements (S and logR'$_{\rm HK}$ indices) for main-sequence late-type stars. To this end, we employ synthetic stellar photospheric spectra combined with varying amounts of chromospheric emission and ISM absorption. We present the effect of ISM absorption on activity measurements by varying several ins…
Modeling Return to Education in Heterogeneous Populations: An Application to Italy
2019
The Mincer human capital earnings function is a regression model that relates individual’s earnings to schooling and experience. It has been used to explain individual behavior with respect to educational choices and to indicate productivity on a large number of countries and across many different demographic groups. However, recent empirical studies have shown that often the population of interest embed latent homogeneous subpopulations, with different returns to education across subpopulations, rendering a single Mincer’s regression inadequate. Moreover, whatever (concomitant) information is available about the nature of such a heterogeneity, it should be incorporated in an appropriate ma…
Book of Short Papers of the 5th international workshop on Models and Learning for Clustering and Classification
2021
The volume contains some papers presented at the 5° workshop on “Models and Learning in Clustering and Classification” organized by the Department of Economics and Business of the University of Catania, Italy in September 2020. The aim of the workshop is two-fold. First, to provide a focus on the state-of-the-art research in the field of statistical models and learning techniques for supervised and unsupervised classification. Secondly, to provide a forum of scientific discussions and comparisons among young and senior researchers in different areas of statistics and data science.