Expository Moments for Pseudo Distributions Expository Moments for Pseudo Distributions
    • USD 119.99

Descripción editorial

This book provides expository derivations for moments of a family of pseudo distributions, which is an extended family of distributions including the pseudo normal (PN) distributions recently proposed by the author. The PN includes the skew normal (SN) derived by A. Azzalini and the closed skew normal (CSN) obtained by A. Domínguez-Molina, G. González-Farías, and A. K. Gupta as special cases. It is known that the CSN includes the SN and other various distributions as special cases, which shows that the PN has a wider variety of distributions. The SN and CSN have symmetric and skewed asymmetric distributions. However, symmetric distributions are restricted to normal ones. On the other hand, symmetric distributions in the PN can be non-normal as well as normal. In this book, for the non-normal symmetric distributions, the term “kurtic normal (KN)” is used, where the coined word “kurtic” indicates “mesokurtic, leptokurtic, or platykurtic” used in statistics. The variety of the PN was made possible using stripe (tigerish) and sectional truncation in univariate and multivariate distributions, respectively. The proofs of the moments and associated results are not omitted and are often given in more than one method with their didactic explanations.

GÉNERO
Ciencia y naturaleza
PUBLICADO
2023
1 de enero
IDIOMA
EN
Inglés
EXTENSIÓN
355
Páginas
EDITORIAL
Springer Nature Singapore
VENDEDOR
Springer Nature B.V.
TAMAÑO
22.6
MB
Statistical Data Analysis and Entropy Statistical Data Analysis and Entropy
2020
Facets of Behaviormetrics Facets of Behaviormetrics
2023
Advanced Studies in Behaviormetrics and Data Science Advanced Studies in Behaviormetrics and Data Science
2020
Pupil Reactions in Response to Human Mental Activity Pupil Reactions in Response to Human Mental Activity
2021
Methods for the Analysis of Asymmetric Proximity Data Methods for the Analysis of Asymmetric Proximity Data
2021
Modern Quantification Theory Modern Quantification Theory
2021