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Autore: | Bolboac? Sorana D |
Titolo: | Applied and Computational Statistics |
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 |
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 |
Opac: | Controlla la disponibilità qui |