STATISTICA & APPLICAZIONI
Six-monthly journal aimed at promoting research in the Methodological Statistics field
Statistica & Applicazioni is a six-monthly journal aimed at promoting research in statistical methodology and its original and innovative applications. Statistica & Applicazioni publishes research articles (and short notes) on theoretical, computational and applied statistics.
The journal is Open Access.
The journal was founded in 2003 by the following Departments belonging to different Italian Universities:
- Quantitative Methods - University of Brescia;
- Quantitative Methods for Business and Economic Sciences - University of Milano-Bicocca;
- Statistics - University of Milano-Bicocca;
- Information Technology and Mathematical Methods - University of Bergamo;
- Economics and Statistics - University of Calabria;
- «Silvio Vianelli» Mathematical and Statistical Sciences - University of Palermo;
- Statistics - Catholic University of the Sacred Heart, Milan.
At present the journal is supported by the following organizations:
- DMS StatLab - University of Brescia
- Department of Statistics and Quantitative Methods - University of Milano-Bicocca
- Department of Statistics - Catholic University of the Sacred Heart, Milan
- Department of Economics, Statistics and Finance - University of Calabria
- Department of Engineering - University of Bergamo
- Az.Agr.Case Basse of Gianfranco Soldera
- Indexed in: Scopus - Google Scholar - Current Index to Statistics - Ulrich's Periodicals Directory - SCImago Journal & Country Rank
- Available on: Torrossa - EBSCO Discovery Service
In this issue
Asymptotic Confidence Intervals for Parameters Estimated through the Ratio of Asymptotically Normal Statistics
In this paper, four different approaches for the definition of asymptotic confidence intervals for the ratio of two unknown parameters are reviewed and compared via a simulation study. The considered approaches are based on the well known Delta Method and on the distribution of the ratio of correlated normal random variables. Simulations concern the ratio between two expectations, the Coefficient of Variation, the Gini Concentration Ratio, and the Sharpe Ratio. It is shown that the asymptotic confidence intervals based on the ratio of correlated normal random variables often have a better coverage accuracy with respect to the ones derived from Delta Method, even if the observed gain is small in some cases.
In this paper, a new sampling technique is proposed that carries more information than contained in ranked set sample (RSS). The proposed sampling technique is defined by making the use for the idea of visual grouping of population units with respect to a fixed threshold and RSS. We refer to it as RSS-Grouping technique. Under the best informative RSS-Grouping technique, the maximum likelihood estimator (MLE) of the mean of an exponential distribution is derived. This MLE is then compared to various candidate estimators through extensive simulation experiments. Numerical results show that the MLE under the best informative RSS-Grouping scheme is preformed better thanthese estimators. The effects of imperfect sampling on the behavior of the MLE under the proposed scheme is also studied. We conduct a simulation study to assess the finite sample behavior of the MLE under imperfect sampling and imperfect classification of visual grouping. Similarly, the simulation study shows that the MLE is behaved asymptotically unbiased. Additionally, the MLE tends to be at least as efficient as the MLE under RSS regardless of raking errors and the estimation of the threshold has slightly effects on the sampling distribution of the MLE.
Childhood is the most relevant period for the formation of food preferences. Political institutions, educational agencies and health professionals are quite interested in the evaluation of the actual knowledge of food quality in children because it offers the opportunity to plan educational actions aimed at promoting the health and quality of life of today’s and tomorrow’s citizens. In this paper, we proposed a questionnaire to measure the level of knowledge of the food quality in children. We selected, as the target population, students of lower secondary schools and we adopted a multidimensional approach to the concept of food quality that involved six dimensions. We investigated the internal construct validity and reliability of the scales developed for these six dimensions applying the Rasch model and a differential item functioning analysis. Moreover, we validated the overall scale of the knowledge of food quality through a Second-order Structural Equation Modelling within a Confirmatory Factor Analysis. The results of our study provide information useful to define and implement educational actions in food quality, in general, or specifically in one or more of food quality dimensions.
One of the key role of a portfolio manager is to identify a suitable asset allocation strategy. The portfolio composition task has to take into account the return and the risk of each asset along with several other factors such as investor’s aims, market expectations and risk tolerance. Thus the final decision making can be naturally viewed as a multiple criteria problem whose solution can benefit from Multiple Criteria Decision Making strategies. In this paper, we propose a two-step multi-criteria approach to support the selection of equity portfolios. Our strategy exploits a varying-coefficient Capital Asset Pricing Model framework. First, we identify clusters of stocks having similar systematic risk factors, then we rank these assets using an ELECTRE III method. We also present a real data example on stocks of S&P500 to illustrate the proposed methodology.
Partial least square path modelling and maximum entropy for the study of entrepreneurship education in naples university
Although successful entrepreneurship education (EE) is possible through the most effective way to manage teachable skills and competencies, there is no universal pedagogical recipe to teach entrepreneurship. This paper attempts to identify the most appropriate teaching methods and addresses the paucity of entrepreneurial outcomes on university experiences in EE. Using a survey of students at a Naples University, it attempts to advance our understanding of an entrepreneurship education program. The study is based on a sample of 665 students and the analysis has been carried out considering joint use of Partial Least squares-path modelling (PLS-PM) and the Generalized Maximum Entropy Estimator (GME). The results show that the entrepreneurial outcome of Entrepreneurship Education programmes is influenced on the satisfaction that students perceive from the educational process. The novel aspects of this paper are: the formalization of an entrepreneurship education program in a Naples University and a methodological point of view involving integration between PLS-PM and GME estimators through PLS reliability measures.
Browse the archive
STATISTICA & APPLICAZIONI - 2018 - 2
STATISTICA & APPLICAZIONI - 2018 - 1