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1. |
Record Nr. |
UNINA9910254094903321 |
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Autore |
Tutz Gerhard |
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Titolo |
Modeling Discrete Time-to-Event Data / / by Gerhard Tutz, Matthias Schmid |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (X, 247 p. 58 illus., 3 illus. in color.) |
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Collana |
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Springer Series in Statistics, , 2197-568X |
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Disciplina |
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Soggetti |
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Statistics |
Biometry |
Social sciences - Statistical methods |
Mathematical statistics - Data processing |
Statistical Theory and Methods |
Biostatistics |
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy |
Statistics and Computing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- The Life Table -- Basic Regression Models -- Evaluation and Model Choice -- Nonparametric Modelling and Smooth Effects -- Tree-Based Approaches -- High-Dimensional Models - Structuring and Selection of Predictors -- Competing Risks Models -- Multiple-Spell Analysis -- Frailty Models and Heterogeneity -- Multiple-Spell Analysis -- List of Examples -- Bibliography -- Subject Index -- Author Index. |
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Sommario/riassunto |
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This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for |
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failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book. . |
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2. |
Record Nr. |
UNINA9910522956703321 |
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Autore |
Rival David E. |
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Titolo |
Biological and Bio-Inspired Fluid Dynamics : Theory and Application / / by David E. Rival |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
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ISBN |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (187 pages) |
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Collana |
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Disciplina |
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Soggetti |
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Fluid mechanics |
Biomedical engineering |
Biotechnology |
Biophysics |
Engineering Fluid Dynamics |
Biomedical Engineering and Bioengineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- Fundamentals -- Scaling -- Internal Flows -- External Flows. |
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Sommario/riassunto |
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This text provides the reader with tools necessary to study biological and bio-inspired flows, all the while developing an appreciation for their evolutionary and engineering constraints. It is suitable for students already exposed to introductory concepts in fluid mechanics and applied mechanics as a whole, but who would not need an advanced training in fluid mechanics per se. Currently no textbook exists that can take students from an introductory position in fluid mechanics to these contemporary topics of interest. The book is ideal for upper-level undergraduates and graduate students studying a range of engineering domains as well as biology, or even medicine. |
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