| Dewey Class |
330.015195 |
| Titolo |
Regression ([Ebook]) : Models, Methods and Applications / by Ludwig Fahrmeir, Thomas Kneib, Stefan Lang, Brian Marx. |
| Autore |
Fahrmeir, Ludwig |
| Added Personal Name |
Kneib, Thomas |
| Lang, Stefan |
| Marx, Brian |
| Other name(s) |
SpringerLink (Online service) |
| Pubblicazione |
Berlin, Heidelberg : Springer |
| , 2013. |
| Physical Details |
XIV, 698 pages : 204 illus. : online resource. |
| ISBN |
9783642343339 |
| Summary Note |
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.: |
| Contents note |
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. |
| System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
| Internet Site |
http://dx.doi.org/10.1007/978-3-642-34333-9 |
| Link alle Opere Legate |
Riferimenti soggetto: .
Bioinformatics .
Econometrics .
Economics .
Mathematical Statistics .
Regression analysis .
Regression analysis — Mathematical models .
Statistical methods .
Authors:
Corporate Authors:
Classification:
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