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Applied and Computational Statistics



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Autore: Bolboac? Sorana D Visualizza persona
Titolo: Applied and Computational Statistics Visualizza cluster
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica: 1 electronic resource (104 p.)
Soggetto non controllato: molecular descriptors
compound symmetry
Anderson–Darling test (AD)
software testing
probability
characteristic polynomial (ChP)
mutation testing
C20 fullerene
fullerene congeners
machine learning
maximum likelihood estimation
gompertz distribution
modified beta generator
structure–property relationships
repeated measurement designs
Monte Carlo simulation
Sommario/riassunto: Research without statistics is like water in the sand; the latter is necessary to reap the benefits of the former. This collection of articles is designed to bring together different approaches to applied statistics. The studies presented in this book are a tiny piece of what applied statistics means and how statistical methods find their usefulness in different fields of research from theoretical frames to practical applications such as genetics, computational chemistry, and experimental design. This book presents several applications of the statistics: A new continuous distribution with five parameters—the modified beta Gompertz distribution; A method to calculate the p-value associated with the Anderson–Darling statistic; An approach of repeated measurement designs; A validated model to predict statement mutations score; A new family of structural descriptors, called the extending characteristic polynomial (EChP) family, used to express the link between the structure of a compound and its properties. This collection brings together authors from Europe and Asia with a specific contribution to the knowledge in regards to theoretical and applied statistics.
Titolo autorizzato: Applied and Computational Statistics  Visualizza cluster
ISBN: 3-03928-177-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910372782403321
Lo trovi qui: Univ. Federico II
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