Parametric Functional Analysis of Variance for Fish Biodiversity Assessment

Battista, Tonio Di; Fortuna, Francesca; Maturo, Fabrizio

doi:10.3808/jei.201600348

Cited by 15 publications

(11 citation statements)

References 29 publications

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“…Society is increasingly demanding environment-friendly businesses. The development of regulations, by imposing sustainable criteria, could limit the discretion of companies in order to protect the environment and the cycle of waste [71][72][73], water [74], and emissions [10,75].…”

Section: Discussionmentioning

confidence: 99%

Relationships between Renewable Energy Consumption, Social Factors, and Health: A Panel Vector Auto Regression Analysis of a Cluster of 12 EU Countries

2020

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One of the key indicators of a population's well-being and the economic development of a country is represented by health, the main proxy for which is life expectancy at birth. Some factors, such as industrialization and modernization, have allowed this to improve considerably. On the other hand, along with high global population growth, the factor which may jeopardize human health the most is environmental degradation, which can be tackled through the transition to renewable energy. The main purpose of our study is to investigate the relationship between renewable energy consumption, social factors, and health, using a Panel Vector Auto Regression (PVAR) technique. We explore the link between some proxy variables for renewable energy consumption, government policy, general public awareness, the market, lobbying activity, the energy dependence on third countries, and health, spanning the period from 1990 to 2015, for a cluster of 12 European countries characterized by common features. Specifically, our analysis shows the importance of having a stringent policy for the development of renewable energy consumption and its influence over other social factors, rather than the existence of causal relationships between health and renewable energy consumption for the analyzed countries. This kind of analysis has a great potential for policy-makers. Further, a deeper understanding of these relationships can create a more effective decision-making process. Sustainability 2020, 12, 2915 2 of 16Concerning the latter, the increasing interest in renewable energy is also due to Europe's dependency on foreign energy sources and to the recent concerns over the volatility of the price of crude oil [8].Moreover, we are currently witnessing an ongoing debate over how to balance the relationships between human health, environmental concerns, and economic development [12][13][14].In this regard, in December 2019 the European Commission presented the European Green Deal, which establishes that the European Union needs to transform itself into a resource-efficient and competitive economy with zero net emissions of greenhouse gases by 2050, and its economic growth should detach itself from resources use. The main objective is to boost the efficient use of resources by moving to a clean, circular economy, and, consequently, stopping climate change, cutting pollution, and improving the health of population [12].Moreover, European Union member countries launched, at the beginning of 2005, the CO 2 emissions trading scheme. Setting environmental taxes is very useful for two reasons. First, they represent an incentive for companies to research and invest in more environmentally friendly technologies, or to deploy fewer resources. Secondly, the increased fiscal revenue resulting from higher tax collection can be used to reduce taxes on labor, savings, and capital, thereby favoring higher investment in environmental conservation [13].Health, the main proxy for which is life expectancy at birth, certainly represents one of the key indicators of ...

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Section: Discussionmentioning

confidence: 99%

Relationships between Renewable Energy Consumption, Social Factors, and Health: A Panel Vector Auto Regression Analysis of a Cluster of 12 EU Countries

2020

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“…Functional ANOVA (FANOVA) Functional data Analysis of Variance, similar to the vector version, contrasts the distance between the mean levels of the factor variables. The aim of this contrast is to find out if the set of functions studied are statistically distinguishable [41]. There will also be Q independent samples X gj (t), j = 1, .…”

Section: Functional Depthsmentioning

confidence: 99%

“…Thus, to assure the indentification of the functional effects α g (t), the sum to zero constraint is introduced [41,44]:…”

Section: Functional Depthsmentioning

confidence: 99%

Application of Functional Data Analysis and FTIR-ATR Spectroscopy to Discriminate Wine Spirits Ageing Technologies

et al. 2020

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Fourier transform infrared spectroscopy (FTIR) with Attenuated Total Reflection (ATR) combined with functional data analysis (FDA) was applied to differentiate aged wine spirits according to the ageing technology (traditional using 250 L wooden barrels versus alternative using micro-oxygenation and wood staves applied in 1000 L stainless steel tanks), the wood species used (chestnut and oak), and the ageing time (6, 12, and 18 months). For this purpose, several features of the wine spirits were examined: chromatic characteristics resulting from the CIELab method, total phenolic index, concentrations of furfural, ellagic acid, vanillin, and coniferaldehyde, and total content of low molecular weight phenolic compounds determined by HPLC. FDA applied to spectral data highlighted the differentiation between all groups of samples, confirming the differentiation observed with the analytical parameters measured. All samples in the test set were differentiated and correctly assigned to the aged wine spirits by FDA. The FTIR-ATR spectroscopy combined with FDA is a powerful methodology to discriminate wine spirits resulting from different ageing technologies.

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“…Third, FDA can tackle cases where data are not sampled at equally spaced time points . Finally, several classical statistical methods can be extended to the infinite‐dimensional context of FDA …”

Section: Introductionmentioning

confidence: 99%

“…19 Finally, several classical statistical methods can be extended to the infinite-dimensional context of FDA. 11,12,[20][21][22][23][24][25] Specifically, in this paper, the FDA approach is proposed for clustering data streams using the k-means algorithm and 3 different semimetrics based on functional principal components (FPCs) decomposition, first and second derivatives, respectively. In the first case, the FPCs decomposition allows capturing the main features of data via a lower-dimensional representation, which preserves the maximum amount of information from the original data.…”

Section: Introductionmentioning

confidence: 99%

Clustering functional data streams: Unsupervised classification of soccer top players based on Google trends

Fortuna

Maturo

Battista

2018

Quality & Reliability Eng

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Nowadays, football teams have become large companies, which produce very high incomes, and the induced gain that may arise from purchasing notorious players has become a crucial aspect for their commercial strategies. The interest for a player is not only exclusively tied to his technical skills but also to other factors, which may attract people not only interested in football. Because soccer has become a fact of life for many supporters, the attention paid to football players is also reflected in the internet traffic. For this reason, the analysis of web data nowadays is a central issue for monitoring players' notoriety and catching information about marketing strategies. This paper aims to provide an original methodological approach for the analysis of web data using the functional data analysis approach. The main advantages of the proposal are the drastic dimensionality reduction of the data and the use of functional tools for obtaining additional information about data. Specifically, in this study, we focus on the problem of clustering data streams using the k‐means algorithm and 3 different semimetrics based on the functional principal components decomposition, first and second derivatives, respectively. An application to a real data set regarding Google queries of 24 football players is proposed for illustrating the method. The final aim of this research is provide scholars, practitioners, football clubs, and agencies interested in planning marketing strategies with additional tools for analyzing web data.

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Parametric Functional Analysis of Variance for Fish Biodiversity Assessment

Cited by 15 publications

References 29 publications

Relationships between Renewable Energy Consumption, Social Factors, and Health: A Panel Vector Auto Regression Analysis of a Cluster of 12 EU Countries

Relationships between Renewable Energy Consumption, Social Factors, and Health: A Panel Vector Auto Regression Analysis of a Cluster of 12 EU Countries

Application of Functional Data Analysis and FTIR-ATR Spectroscopy to Discriminate Wine Spirits Ageing Technologies

Clustering functional data streams: Unsupervised classification of soccer top players based on Google trends

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