Statistical Modeling and Applications

Multivariate, Heavy-Tailed, Skewed Distributions and Mixture Modeling, Volume 2 de

,

Éditeur :

Springer


Paru le : 2024-12-17

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Description

In an era defined by the seamless integration of data and sophisticated analytical and modeling techniques, the quest for advanced statistical modeling and methodologies has never been more pertinent. Statistical Modeling and Applications: Multivariate, Heavy-Tailed, Skewed Distributions, Mixture and Neural-Network Modeling, Volume 2, represents a concerted effort to bridge the gap between theoretical advancements and practical applications in the realm of Statistical Science, namely in the area of Statistical Modeling. It also aims to present a wide range of emerging topics in mathematical and statistical modeling written by a group of distinguished researchers from top-tier universities and research institutes to offer broader opportunities in stimulating further collaborations in the areas of mathematics and statistics.
The book has eleven chapters, divided in two Parts, with Part I comprising five chapters dealing with the application of Multivariate Analysis techniques and multivariate distributions to a set of different situations, and Part II consisting of six chapters which address the modeling of several interesting phenomena through the use of Heavy-Tailed, Skewed, Circular-Linear and Mixture Distributions, as well as Neural Networks.
Pages
250 pages
Collection
n.c
Parution
2024-12-17
Marque
Springer
EAN papier
9783031696213
EAN PDF
9783031696220

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
12933 Ko
Prix
210,99 €
EAN EPUB
9783031696220

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
27197 Ko
Prix
210,99 €

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