2025
Autores
Figueiredo F.O.; Figueiredo A.; Gomes M.I.;
Publicação
Data Analysis and Related Applications 5 Models Methods and Techniques Volume 13
Abstract
Data sets that contain an excessive number of zeros appear in several fields of applications. This chapter considers a zero-inflated Lomax distribution as a possible model for these types of data, and presents and analyzes the performance of a Shewhart control chart for process monitoring. Several approaches allow for frequent zero observations, and among them, the most common are zero-inflated models and hurdle models in case of count data, and the use of zero-inflated distributions to model semi-continuous data, that is, data from a continuous distribution with one or more than one point of mass. The chapter presents some motivation for the use of the zero-inflated Lomax distribution together with some properties of this distribution. It proposes a Shewhart-type control chart for monitoring zero-inflated Lomax data, and analyzes its performance under some scenarios.
2025
Autores
Figueiredo, FO; Figueiredo, AMS;
Publicação
Research in Statistics
Abstract
This data-based study aims to understand the progress made by EU countries in recent years on key areas of the circular economy by analyzing some indicators. The data have been collected from the Eurostat database over the period 2013-2021. After a preliminary analysis of the data set, a double principal component analysis has been used. This approach provides insights into the evolution of the countries and correlations between the indicators, highlighting which EU countries are the most (or least) similar to each other. The findings of this study indicate that EU countries collectively have advanced towards a circular economy in various indicators, with certain countries showing more notable progress than others. Some countries are even considered outliers, for positive or negative reasons, in some of the indicators. Overall, the Western EU countries perform better than the Eastern countries on most of the indicators analyzed, especially for resource productivity, municipal waste management, circularity rate, private investment in the circular economy sectors, and gross added value in circular economy sectors. The exceptions are for the generation of municipal waste, percentage of persons employed in circular economy sectors, and greenhouse gas emissions, the ones where the Eastern countries in general perform better. © 2025 Elsevier B.V., All rights reserved.
2025
Autores
Figueiredo, A;
Publicação
Springer Proceedings in Mathematics and Statistics
Abstract
We propose an approach to cluster and classify compositional data. We transform the compositional data into directional data using the square root transformation. To cluster the compositional data, we apply the identification of a mixture of Watson distributions on the hypersphere and to classify the compositional data into predefined groups, we apply Bayes rules based on the Watson distribution to the directional data. We then compare our clustering results with those obtained in hierarchical clustering and in the K-means clustering using the log-ratio transformations of the data and compare our classification results with those obtained in linear discriminant analysis using log-ratio transformations of the data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
2025
Autores
Espanhol, R; Jacinto Soares, C; MPM Oliveira, B; Torres, D; João Gregório, M;
Publicação
Acta Portuguesa de Nutrição
Abstract
2025
Autores
Caetano, E; MPM Oliveira, B; Correia, F; Torres, D; Poínhos, R;
Publicação
Acta Portuguesa de Nutrição
Abstract
2025
Autores
Alexandre, MR; Poinhos, R; Oliveira, BMPM; Correia, F;
Publicação
NUTRIENTS
Abstract
Background/Objectives: Obesity is a major contributor to cardiovascular disease, yet traditional risk assessment methods may overlook behavioral and circadian influences that modulate metabolic health. Chronotype, physical activity, sleep quality, eating speed, and breakfast habits have been increasingly associated with cardiometabolic outcomes. This study aims to evaluate the associations between these behavioral factors and both anthropometric and biochemical markers of cardiovascular risk among obese candidates for bariatric surgery. Methods: A cross-sectional study was conducted in a sample of 286 obese adults (78.3% females, mean 44.3 years, SD = 10.8, mean BMI = 42.5 kg/m2, SD = 6.2) followed at a central Portuguese hospital. Chronotype (reduced Morningness-Eveningness Questionnaire), sleep quality (Pittsburgh Sleep Quality Index), physical activity (Godin-Shephard Questionnaire), eating speed, and breakfast skipping were assessed. Cardiovascular risk markers included waist-to-hip ratio (WHR), waist-to-height ratio, A Body Shape Index (ABSI), Body Roundness Index, atherogenic index of plasma (AIP), triglyceride-glucose index (TyG), and homeostatic model assessment for insulin resistance (HOMA-IR). Results: Men exhibited significantly higher WHR, ABSI, HOMA-IR, TyG, and AIP. Eveningness was associated with higher insulin (r = -0.168, p = 0.006) and HOMA-IR (r = -0.156, p = 0.011). Poor sleep quality was associated with higher body fat mass (r = 0.151, p = 0.013), total cholesterol (r = 0.169, p = 0.005) and LDL cholesterol (r = 0.132, p = 0.030). Faster eating speed was associated with a higher waist circumference (r = 0.123, p = 0.038) and skeletal muscle mass (r = 0.160, p = 0.009). Conclusions: Male sex, evening chronotype, and poor sleep quality were associated with more adverse cardiometabolic profiles in individuals with severe obesity. These findings support the integration of behavioral and circadian factors into cardiovascular risk assessment strategies.
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