TY - BOOK ID - 146152564 TI - Symmetric and Asymmetric Distributions : Theoretical Developments and Applications PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Humanities KW - Social interaction KW - positive and negative skewness KW - ordering KW - fitting distributions KW - Epsilon-skew-Normal KW - Epsilon-skew-Cauchy KW - bivariate densities KW - generalized Cauchy distributions KW - asymmetric bimodal distribution KW - bimodal KW - maximum likelihood KW - slashed half-normal distribution KW - kurtosis KW - likelihood KW - EM algorithm KW - flexible skew-normal distribution KW - skew Birnbaum–Saunders distribution KW - bimodality KW - maximum likelihood estimation KW - Fisher information matrix KW - maximum likelihood estimates KW - type I and II censoring KW - skewness coefficient KW - Weibull censored data KW - truncation KW - half-normal distribution KW - probabilistic distribution class KW - normal distribution KW - identifiability KW - moments KW - power-normal distribution KW - positive and negative skewness KW - ordering KW - fitting distributions KW - Epsilon-skew-Normal KW - Epsilon-skew-Cauchy KW - bivariate densities KW - generalized Cauchy distributions KW - asymmetric bimodal distribution KW - bimodal KW - maximum likelihood KW - slashed half-normal distribution KW - kurtosis KW - likelihood KW - EM algorithm KW - flexible skew-normal distribution KW - skew Birnbaum–Saunders distribution KW - bimodality KW - maximum likelihood estimation KW - Fisher information matrix KW - maximum likelihood estimates KW - type I and II censoring KW - skewness coefficient KW - Weibull censored data KW - truncation KW - half-normal distribution KW - probabilistic distribution class KW - normal distribution KW - identifiability KW - moments KW - power-normal distribution UR - https://www.unicat.be/uniCat?func=search&query=sysid:146152564 AB - 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. ER -