1,720,981 research outputs found
Non-parametric probability distributions embedded inside of a linear space provided with a quadratic metric
No full textFuzzy Regression Models with Fuzzy Random Variables: Application in the Social and Economic Fields
No full textThe human capital stock of the firm, accumulated through educational and training activities, is one of the main factors of production and economic growth. From the firm’s perspective, the aim of the human capital investment is to increase productivity; instead, for the employees, the primary aims of the education and training are the effects on their wages and carriers. Our paper focuses on the analysis of the determinants that can affect the performance of employees in a training course. In particular, it is proposed a fuzzy regression model to analyze the dependence of the dependent variable "vote" by some independent fuzzy and crisp variables
Building Statistical Indicators of Equitable and Sustainable Well-Being in a Functional Framework
No full textIn recent decades, the role of gross domestic product (GDP) as an indicator of well-being has been sharply questioned by both researchers and institutions. This theoretical discussion leads to the international debate “Beyond GDP”, which aims to assess the progress of a country considering fundamental social and environmental dimensions of well-being, inequality, and sustainability. According to this perspective, well-being and quality of life, in general, deserve great attention at the institutional level; hence, this topic attracted the consideration of methodological researchers, and thus many statistical indicators have been proposed. Recently, most insiders have dealt with the problem of the multidimensionality of well-being, and many research has also stressed the importance of assessing trends and changes over time rather than observing indices in single instants. For this reason, this research proposes the use of functional data analysis to build new social indicators of well-being and to interpret them considering the original time observations as a continuous function. Indeed, repeated measures of social indicators of well-being can be considered as functions in the time domain. Moreover, this approach adds to the existing techniques interesting instruments of analysis, e.g. the derivatives and the functional principal components, and overcomes some strong assumptions of the time series analysis. To demonstrate the appropriateness of this approach, this study proposes an application to real data concerning “subjective well-being” within the Italian “BES project” The final aim of this research is to provide scholars and policy-makers with additional tools for assessing the “Equitable and Sustainable Well-being” over time
Random Survival Forest for Censored Functional Data
No full textThis article introduces a Random Survival Forest (RSF) method for functional data. The focus is specifically on defining a new functional data structure, the Censored Functional Data (CFD), for addressing the challenge of accurately modelling time-to-event data in the presence of censoring and irregular temporal structures. Traditional survival models struggle to incorporate complex functional patterns, making the proposed approach particularly valuable for improving prediction and interpretation. This approach allows for precise modelling of functional survival trajectories, leading to improved interpretation and prediction of survival dynamics across different groups. A medical survival study on the benchmark Sequential Organ Failure Assessment (SOFA) dataset and an extensive simulation study are presented. Results show good performance of the proposed approach, particularly in ranking the importance of predicting variables
Diversity in the Social and Economic Science: Review and Application
No full textBoard diversity is an important mechanism of corporate governance in order to ensure the efficacy of the management and monitoring actions. A large number of empirical studies and the European Commission identify board diversity as an important indicator of success for international corporate practice. Although many indices have been proposed to evaluate diversity, no universally accepted measure has yet been established. Even in ecology, diversity, meant as bio-diversity, is a very important aspect in assessing the quality of the environment; for this reason, also in this field, numerous indices have been proposed. This paper aims to make a review and a comparison between the diversity indices proposed in the two areas and understand what are the limitations and advantages of the indices proposed in recent decades
Supervised learning from high-dimensional data through dynamic updating of functional classification rules
No full textTesting Equality of Functions Across Multiple Experimental Conditions for Different Ability Levels in the IRT Context: the Case of the IPRASE TLT 2016 Survey.
No full textExploring intertemporal decision-making dynamics through functional data analysis: investigating variations in different discount function's dimensions
No full textIntertemporal preferences are closely related to essential aspects of an individual’s emotional and cognitive domains. Discount functions are used to quantify these preferences, which can help us understand conditions such as addiction, depression, and Attention Deficit Hyperactivity Disorder (ADHD). However, traditional parametric models are limited when dealing with intertemporal preferences, mainly when behavioural biases are involved. This study exploits Functional Data Analysis (FDA) to investigate the properties of discount functions in intertemporal choices comparing people suffering from the Hikikomori pathology (a condition that involves social withdrawal) and normal people. Notably, the goal of this research is to look for statistically significant differences in the dynamics of intertemporal decision-making according to different gravity of the Hikikomori condition through the magnified FDA lens on different functional dimensions; the distinctive curves of discount functions categorised by Hikikomori scores prompted a more profound investigation via the so-called augmented functional analysis of variance. The original curves and their derivatives, and the discount rates and their first derivatives provide the different functional dimensions explored. This original approach of analyzing differences between subgroups according to decision-making behaviours is exciting from a methodological and practical perspective
Population attributable fraction for continuously distributed exposures
No full textWhen estimating population attributable fractions (PAF), it is common to partition a naturally continuous exposure into a categorical risk factor. While prior risk factor categorization can help estimation and interpretation, it can result in underestimation of the disease burden attributable to the exposure as well as biased comparisons across different exposures and risk factors. Here, we propose sensible PAF estimands for continuous exposures under a potential outcomes framework. In contrast to previous approaches, we incorporate estimation of the minimum risk exposure value (MREV) into our procedures. While for exposures such as tobacco usage, a sensible value of the MREV is known, often it is unknown and needs to be estimated. Second, in the setting that the MREV value is an extreme-value of the exposure lying in the distributional tail, we argue that the natural estimator of PAF may be both statistically biased and highly volatile; instead, we consider a family of modified PAFs which include the natural estimate of PAF as a limit. A graphical comparison of this set of modified PAF for differing risk factors may be a better way to rank risk factors as intervention targets, compared to the standard PAF calculation. Finally, we analyse the bias that may ensue from prior risk factor categorization, examining whether categorization is ever a good idea, and suggest interpretations of categorized-estimands within a causal inference setting
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