TY  - BOOK
AU  - Fahrmeir,Ludwig
AU  - Kneib,Thomas
AU  - Lang,Stefan
AU  - Marx,Brian
ED  - SpringerLink (Online service)
TI  - Regression: Models, Methods and Applications 
SN  - 9783642343339
AV  - QA276-280 
U1  - 330.015195 23
PY  - 2013///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Statistics
KW  - Epidemiology
KW  - Biostatistics
KW  - Econometrics
KW  - Statistics for Business/Economics/Mathematical Finance/Insurance
KW  - Statistical Theory and Methods
KW  - Statistics, general
KW  - Electronic books
KW  - local
N1  - 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
N2  - 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
UR  - http://ezproxy.alfaisal.edu/login?url=http://dx.doi.org/10.1007/978-3-642-34333-9
ER  -