Atnaujinkite slapukų nuostatas

El. knyga: Expository Moments for Pseudo Distributions

Kitos knygos pagal šią temą:
Expository Moments for Pseudo DistributionsDidesnis paveikslėlis
Kitos knygos pagal šią temą:

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

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. Domķnguez-Molina, G. Gonzįlez-Farķas, 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.





 
The Sectionally Truncated Normal Distribution.- Normal Moments Under
Stripe Truncation and the Real-Valued Poisson Distribution.- The Basic
Parabolic Cylinder Distribution and its Multivariate Extension.- The
Pseudo-Normal (PN) Distribution.- The Kurtic-Normal (KN) Distribution.- The
Normal-Normal (NN) Distribution.- The Decompositions of the PN and NN
Distributed Variables.- The Truncated Pseudo-Normal (TPN) and Truncated
Normal-Normal (TNN) Distributions.- The Student t- and Pseudo-t (PT)
Distributions: Various Expressions of Mixtures.- Multivariate Measures of
Skewness and Kurtosis.
Haruhiko Ogasawara is Professor Emeritus, Otaru University of Commerce.
Daugiau apie elektronines knygas Daugiau apie elektronines knygas
Pastovi nuoroda: https://www.kriso.lt/db/97898119352512e.html
Raktažodžiai: