On Corrado Gini's 1932 paper "Intorno alle curve di concentrazione". A selection of translated excerpts

The main focus of the paper is the study of the concentration curve, with special emphasis on its fundamental features and properties and on the relationship with other relevant curves. One of the most innovative contributions (rediscovered forty years later) is the alternative analytical representation of the concentration curves in a coordinate system which assumes the so-called equidistribution line as x-axis and its perpendicular line as y-axis. Furthermore, the impact of the presence of a superior and/or inferior limit in the variable of interest on the maximum concentration triangle is examined. Suitable correction coefficients are derived for computing the corresponding concentration ratio, that take into account these restrictions

Deep learning for supervised classification

One of the most recent area in the Machine Learning research is Deep Learning. Deep Learning algorithms have been applied successfully to computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics. The key idea of Deep Learning is to combine the best techniques from Machine Learning to build powerful general‑purpose learning algorithms. It is a mistake to identify Deep Neural Networks with Deep Learning Algorithms. Other approaches are possible, and in this paper we illustrate a generalization of Stacking which has very competitive performances. In particular, we show an application of this approach to a real classification problem, where a three-stages Stacking has proved to be very effective

Statistics in the Big Data era

It is estimated that about 90% of the currently available data have been produced over the last two years. Of these, only 0.5% is effectively analysed and used. However, this data can be a great wealth, the oil of 21st century, when analysed with the right approach. In this article, we illustrate some specificities of these data and the great interest that they can represent in many fields. Then we consider some challenges to statistical analysis that emerge from their analysis, suggesting some strategies

Bonferroni and Gini indices for various parametric families of distributions

The Bonferroni index (BI) and Bonferroni curve (BC) have assumed relief not only in economics to study income and poverty, but also in other fields like reliability, demography, insurance and medicine. Besides, the increasingly frequent comparison with the Lorenz curve (LC) and Gini index (GI) both in theoretical and applied studies has driven us to derive explicit expressions for BI, BC, GI and LC for some thirty five continuous distributions. It is expected that these expressions could provide a useful reference and encourage further research within the aforementioned fields

A proposal of poverty measures based on the Bonferroni inequality index

Bonferroni inequality index, Gini concentration ratio, Sen and Dagum poverty measures, Pigou-Dalton transfer principle

A look at the Bonferroni inequality measure in a reliability framework

Bonferroni Index, Inequality Measure, Reliability

Bayesian estimation of the Bonferroni index from a Pareto-type I population

Bonferroni index, Bayes estimator, Pareto-type I distribution, truncated Erlag distribution, squared error loss function

Sourcing Hydrogen for the Production of Sustainable Aviation Fuels

Sustainable aviation fuels (SAFs) are the near-term technological solution to decarbonize the aviation industry sector. There are several pathways to obtain biojet fuels, which can be classified into four main categories, namely oil-to-jet, alcohol-to-jet, gas-to-jet, and sugar-to-jet. All of them share the need for hydrogen to obtain a drop-in fuel that can be blended with petroleum-based jet fuel. The hydrogen input requirements affect the life cycle greenhouse gas emissions, increase the biojet fuel cost and hinder the construction of distributed processing plants. This study addresses the problem of hydrogen sourcing in the production of SAFs through a systematic literature review. Techno-economic studies of biojet fuel production using different feedstocks and conversion pathways are analyzed focusing on the methods of hydrogen provision. The technological options used to generate the required hydrogen within the conversion process itself as well as externally, along with the main strategies to reduce the hydrogen demand are identified. The production yields and the hydrogen consumption of several SAF production pathways are compared. The jet fuel yields reach values as high as 0.66 for hydroprocessing of vegetable oils with external hydrogen provision, while they drop to 0.10 for production from lignocellulosic biomass with internal hydrogen sourcing. The results of the analysis highlight the real potential of four among the most promising routes for the production of biojet fuels when the burden related to hydrogen demand is properly taken into account

Encounter with the Italian Statistical School: A conversation with Carlo Benedetti

Scientific and human characteristics of Gini, Bonferroni, Georgescu-Roegen and Konus

A methodological survey of recent studies for the measurement of inequality of economic welfare carried out by some Italian statisticians

inequality measurement, welfare, Italian contributions