Articoli correlati a Regression: Models, Methods and Applications
Sinossi
Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric 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 numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book's dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented.
The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference.
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 at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
(nessuna copia disponibile)
Cerca: Inserisci un desiderataNon riesci a trovare il libro che stai cercando? Continueremo a cercarlo per te. Se uno dei nostri librai lo aggiunge ad AbeBooks, ti invieremo una notifica!
Inserisci un desiderata
