Symmetric and Asymmetric Distributions
Title | Symmetric and Asymmetric Distributions PDF eBook |
Author | Emilio Gómez Déniz |
Publisher | MDPI |
Pages | 146 |
Release | 2021-01-21 |
Genre | Social Science |
ISBN | 3039366467 |
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.
Symmetric and Asymmetric Distributions
Title | Symmetric and Asymmetric Distributions PDF eBook |
Author | Emilio Gómez Déniz |
Publisher | |
Pages | 146 |
Release | 2020 |
Genre | |
ISBN | 9783039366477 |
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.
Symmetric Multivariate and Related Distributions
Title | Symmetric Multivariate and Related Distributions PDF eBook |
Author | Kai Wang Fang |
Publisher | CRC Press |
Pages | 165 |
Release | 2018-01-18 |
Genre | Mathematics |
ISBN | 1351093940 |
Since the publication of the by now classical Johnson and Kotz Continuous Multivariate Distributions (Wiley, 1972) there have been substantial developments in multivariate distribution theory especially in the area of non-normal symmetric multivariate distributions. The book by Fang, Kotz and Ng summarizes these developments in a manner which is accessible to a reader with only limited background (advanced real-analysis calculus, linear algebra and elementary matrix calculus). Many of the results in this field are due to Kai-Tai Fang and his associates and appeared in Chinese publications only. A thorough literature search was conducted and the book represents the latest work - as of 1988 - in this rapidly developing field of multivariate distributions. The authors are experts in statistical distribution theory.
Statistics For Dummies
Title | Statistics For Dummies PDF eBook |
Author | Deborah J. Rumsey |
Publisher | John Wiley & Sons |
Pages | 423 |
Release | 2016-06-07 |
Genre | Mathematics |
ISBN | 1119293529 |
The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.
The Laplace Distribution and Generalizations
Title | The Laplace Distribution and Generalizations PDF eBook |
Author | Samuel Kotz |
Publisher | Springer Science & Business Media |
Pages | 358 |
Release | 2012-12-06 |
Genre | Mathematics |
ISBN | 146120173X |
This book describes the inferential and modeling advantages that this distribution, together with its generalizations and modifications, offers. The exposition systematically unfolds with many examples, tables, illustrations, and exercises. A comprehensive index and extensive bibliography also make this book an ideal text for a senior undergraduate and graduate seminar on statistical distributions, or for a short half-term academic course in statistics, applied probability, and finance.
Digital Foundations
Title | Digital Foundations PDF eBook |
Author | xtine burrough |
Publisher | Peachpit Press |
Pages | 563 |
Release | 2008-12-11 |
Genre | |
ISBN | 0132104237 |
Fuses design fundamentals and software training into one cohesive book! The only book to teach Bauhaus design principles alongside basic digital tools of Adobe's Creative Suite, including the recently released Adobe CS4 Addresses the growing trend of compressing design fundamentals and design software into the same course in universities and design trade schools. Lessons are timed to be used in 50-minute class sessions. Digital Foundations uses formal exercises of the Bauhaus to teach the Adobe Creative Suite. All students of digital design and production—whether learning in a classroom or on their own—need to understand the basic principles of design in order to implement them using current software. Far too often design is left out of books that teach software. Consequently, the design software training exercise is often a lost opportunity for visual learning. Digital Foundations reinvigorates software training by integrating Bauhaus design exercises into tutorials fusing design fundamentals and core Adobe Creative Suite methodologies. The result is a cohesive learning experience. Design topics and principles include: Composition; Symmetry and Asymmetry; Gestalt; Appropriation; The Bauhaus Basic Course Approach; Color Theory; The Grid; Scale, Hierarchy and Collage; Tonal Range; Elements of Motion. Digital Foundations is an AIGA Design Press book, published under Peachpit's New Riders imprint in partnership with AIGA, the professional association for design.
An Asymmetric Distribution with Zero Skewness
Title | An Asymmetric Distribution with Zero Skewness PDF eBook |
Author | Erik Meijer |
Publisher | |
Pages | 3 |
Release | 2014 |
Genre | |
ISBN |
We give an example of an asymmetric distribution with zero skewness.Zero skewness is often taken to mean that the distribution is asymmetric. However, this is not correct. There exist asymmetric distributions that have zero third central moment. Here we give an example. First, we give the definition of a symmetric and an asymmetric distribution.