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Regression : Models, Methods and Applications / / by Ludwig Fahrmeir, Thomas Kneib, Stefan Lang, Brian Marx



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Autore: Fahrmeir L. Visualizza persona
Titolo: Regression : Models, Methods and Applications / / by Ludwig Fahrmeir, Thomas Kneib, Stefan Lang, Brian Marx Visualizza cluster
Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013
Edizione: 1st ed. 2013.
Descrizione fisica: 1 online resource (828 p.)
Disciplina: 519.536
Soggetto topico: Statistics
Econometrics
Biometry
Epidemiology
Statistics in Business, Management, Economics, Finance, Insurance
Statistical Theory and Methods
Biostatistics
Persona (resp. second.): KneibThomas
LangStefan
MarxBrian
Note generali: Description based upon print version of record.
Nota di contenuto: Introduction -- Regression Models -- The Classical Linear Model -- Extensions of the Classical Linear Model -- Generalized Linear Models -- Categorical Regression Models -- Mixed Models -- Nonparametric Regression -- Structured Additive Regression -- Quantile Regression -- A Matrix Algebra -- B Probability Calculus and Statistical Inference -- Bibliography -- Index.
Sommario/riassunto: The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference.
Titolo autorizzato: Regression  Visualizza cluster
ISBN: 9783642343339
3642343333
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910438158603321
Lo trovi qui: Univ. Federico II
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