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Research without statistics is like water in the sand; the latter is necessary to reap the benefits of the former. This collection of articles is designed to bring together different approaches to applied statistics. The studies presented in this book are a tiny piece of what applied statistics means and how statistical methods find their usefulness in different fields of research from theoretical frames to practical applications such as genetics, computational chemistry, and experimental design. This book presents several applications of the statistics: A new continuous distribution with five parameters—the modified beta Gompertz distribution; A method to calculate the p-value associated with the Anderson–Darling statistic; An approach of repeated measurement designs; A validated model to predict statement mutations score; A new family of structural descriptors, called the extending characteristic polynomial (EChP) family, used to express the link between the structure of a compound and its properties. This collection brings together authors from Europe and Asia with a specific contribution to the knowledge in regards to theoretical and applied statistics.

molecular descriptors --- compound symmetry --- Anderson–Darling test (AD) --- software testing --- probability --- characteristic polynomial (ChP) --- mutation testing --- C20 fullerene --- fullerene congeners --- machine learning --- maximum likelihood estimation --- gompertz distribution --- modified beta generator --- structure–property relationships --- repeated measurement designs --- Monte Carlo simulation

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In recent years, the advances and abilities of computer software have substantially increased the number of scientific publications that seek to introduce new probabilistic modelling frameworks, including continuous and discrete approaches, and univariate and multivariate models. Many of these theoretical and applied statistical works are related to distributions that try to break the symmetry of the normal distribution and other similar symmetric models, mainly using Azzalini's scheme. This strategy uses a symmetric distribution as a baseline case, then an extra parameter is added to the parent model to control the skewness of the new family of probability distributions. The most widespread and popular model is the one based on the normal distribution that produces the skewed normal distribution. In this Special Issue on symmetric and asymmetric distributions, works related to this topic are presented, as well as theoretical and applied proposals that have connections with and implications for this topic. Immediate applications of this line of work include different scenarios such as economics, environmental sciences, biometrics, engineering, health, etc. This Special Issue comprises nine works that follow this methodology derived using a simple process while retaining the rigor that the subject deserves. Readers of this Issue will surely find future lines of work that will enable them to achieve fruitful research results.

Humanities --- Social interaction --- positive and negative skewness --- ordering --- fitting distributions --- Epsilon-skew-Normal --- Epsilon-skew-Cauchy --- bivariate densities --- generalized Cauchy distributions --- asymmetric bimodal distribution --- bimodal --- maximum likelihood --- slashed half-normal distribution --- kurtosis --- likelihood --- EM algorithm --- flexible skew-normal distribution --- skew Birnbaum–Saunders distribution --- bimodality --- maximum likelihood estimation --- Fisher information matrix --- maximum likelihood estimates --- type I and II censoring --- skewness coefficient --- Weibull censored data --- truncation --- half-normal distribution --- probabilistic distribution class --- normal distribution --- identifiability --- moments --- power-normal distribution --- positive and negative skewness --- ordering --- fitting distributions --- Epsilon-skew-Normal --- Epsilon-skew-Cauchy --- bivariate densities --- generalized Cauchy distributions --- asymmetric bimodal distribution --- bimodal --- maximum likelihood --- slashed half-normal distribution --- kurtosis --- likelihood --- EM algorithm --- flexible skew-normal distribution --- skew Birnbaum–Saunders distribution --- bimodality --- maximum likelihood estimation --- Fisher information matrix --- maximum likelihood estimates --- type I and II censoring --- skewness coefficient --- Weibull censored data --- truncation --- half-normal distribution --- probabilistic distribution class --- normal distribution --- identifiability --- moments --- power-normal distribution

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In recent years, the advances and abilities of computer software have substantially increased the number of scientific publications that seek to introduce new probabilistic modelling frameworks, including continuous and discrete approaches, and univariate and multivariate models. Many of these theoretical and applied statistical works are related to distributions that try to break the symmetry of the normal distribution and other similar symmetric models, mainly using Azzalini's scheme. This strategy uses a symmetric distribution as a baseline case, then an extra parameter is added to the parent model to control the skewness of the new family of probability distributions. The most widespread and popular model is the one based on the normal distribution that produces the skewed normal distribution. In this Special Issue on symmetric and asymmetric distributions, works related to this topic are presented, as well as theoretical and applied proposals that have connections with and implications for this topic. Immediate applications of this line of work include different scenarios such as economics, environmental sciences, biometrics, engineering, health, etc. This Special Issue comprises nine works that follow this methodology derived using a simple process while retaining the rigor that the subject deserves. Readers of this Issue will surely find future lines of work that will enable them to achieve fruitful research results.

positive and negative skewness --- ordering --- fitting distributions --- Epsilon-skew-Normal --- Epsilon-skew-Cauchy --- bivariate densities --- generalized Cauchy distributions --- asymmetric bimodal distribution --- bimodal --- maximum likelihood --- slashed half-normal distribution --- kurtosis --- likelihood --- EM algorithm --- flexible skew-normal distribution --- skew Birnbaum–Saunders distribution --- bimodality --- maximum likelihood estimation --- Fisher information matrix --- maximum likelihood estimates --- type I and II censoring --- skewness coefficient --- Weibull censored data --- truncation --- half-normal distribution --- probabilistic distribution class --- normal distribution --- identifiability --- moments --- power-normal distribution

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During the third decade of the 21st century, human societies across the world are facing significant water-related problems, such as ecosystem degradation, groundwater depletion, natural and anthropogenic droughts and floods, water-borne health issues, and deforestation. These problems are exacerbated by climate change, a phenomenon that has been accelerated due to human intervention in natural systems since the industrial revolution. There is an urgent need to better understand the interaction of hydrological systems in terms of climate variability and the anthropogenic factors that contribute to the dynamics and resilience of coupled human–water systems and effective risk management in the area of water resource management. Socio-hydrology is an interdisciplinary field that integrates natural and social sciences and aims to study the long-term dynamics of bidirectional feedback in coupled human–water systems. This book on socio-hydrology aims to compile cross-disciplinary scientific endeavors and innovations in research on the development, education, and application of coupled human–water systems. The articles published in this book represent diverse and broad aspects of water management in the context of socio-hydrology systems around the globe. The articles and ideas presented in this book represent a significant source of references for interdisciplinary water science programs and provide an excellent guide for experts involved in the future planning and management of water resources. This book is dedicated to friends of the Green Water-Infrastructure Academy and those who pursue cross-disciplinary water research, education, and management.

Research & information: general --- digital elevation model --- maximum likelihood estimation (MLE) classification --- runoff quality --- social, economic and environmental (SEE) factor --- Triangulated Irregular Network (TIN) --- urbanization --- vegetation density --- stormwater management --- social factors --- green stormwater infrastructure --- society --- risk analysis --- water-related crises --- resilience --- security --- floods --- drinking water --- crisis planning --- landslides --- logistic regression --- slope gradient --- land use --- soil --- Coonoor --- behavior --- trust --- risk --- tap water --- salience --- common pool resources --- integrated water management --- water governance --- water resilience --- socio-hydrology --- irrigation efficiency --- surface water-groundwater interactions --- sustainability --- knowledge coproduction --- integrated local environmental knowledge --- education and training --- community-based water development --- Black Sea --- coastal tourism --- regional climate change --- warming --- wind --- waves --- sea level rise --- upwelling --- heavy rain --- river plume --- algal bloom --- introduced species --- digital elevation model --- maximum likelihood estimation (MLE) classification --- runoff quality --- social, economic and environmental (SEE) factor --- Triangulated Irregular Network (TIN) --- urbanization --- vegetation density --- stormwater management --- social factors --- green stormwater infrastructure --- society --- risk analysis --- water-related crises --- resilience --- security --- floods --- drinking water --- crisis planning --- landslides --- logistic regression --- slope gradient --- land use --- soil --- Coonoor --- behavior --- trust --- risk --- tap water --- salience --- common pool resources --- integrated water management --- water governance --- water resilience --- socio-hydrology --- irrigation efficiency --- surface water-groundwater interactions --- sustainability --- knowledge coproduction --- integrated local environmental knowledge --- education and training --- community-based water development --- Black Sea --- coastal tourism --- regional climate change --- warming --- wind --- waves --- sea level rise --- upwelling --- heavy rain --- river plume --- algal bloom --- introduced species

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This book addresses contemporary statistical inference issues when no or minimal assumptions on the nature of studied phenomenon are imposed. Information theory methods play an important role in such scenarios. The approaches discussed include various high-dimensional regression problems, time series and dependence analyses.

Technology: general issues --- History of engineering & technology --- Mechanical engineering & materials --- high-dimensional time series --- nonstationarity --- network estimation --- change points --- kernel estimation --- high-dimensional regression --- loss function --- random predictors --- misspecification --- consistent selection --- subgaussianity --- generalized information criterion --- robustness --- statistical learning theory --- information theory --- entropy --- parameter estimation --- learning systems --- privacy --- prediction methods --- misclassification risk --- model misspecification --- penalized estimation --- supervised classification --- variable selection consistency --- archimedean copula --- consistency --- estimation --- extreme-value copula --- tail dependency --- multivariate analysis --- conditional mutual information --- CMI --- information measures --- nonparametric variable selection criteria --- gaussian mixture --- conditional infomax feature extraction --- CIFE --- joint mutual information criterion --- JMI --- generative tree model --- Markov blanket --- minimum distance estimation --- maximum likelihood estimation --- influence functions --- adaptive splines --- B-splines --- right-censored data --- semiparametric regression --- synthetic data transformation --- time series --- high-dimensional time series --- nonstationarity --- network estimation --- change points --- kernel estimation --- high-dimensional regression --- loss function --- random predictors --- misspecification --- consistent selection --- subgaussianity --- generalized information criterion --- robustness --- statistical learning theory --- information theory --- entropy --- parameter estimation --- learning systems --- privacy --- prediction methods --- misclassification risk --- model misspecification --- penalized estimation --- supervised classification --- variable selection consistency --- archimedean copula --- consistency --- estimation --- extreme-value copula --- tail dependency --- multivariate analysis --- conditional mutual information --- CMI --- information measures --- nonparametric variable selection criteria --- gaussian mixture --- conditional infomax feature extraction --- CIFE --- joint mutual information criterion --- JMI --- generative tree model --- Markov blanket --- minimum distance estimation --- maximum likelihood estimation --- influence functions --- adaptive splines --- B-splines --- right-censored data --- semiparametric regression --- synthetic data transformation --- time series