Semiparametric Regression
By: Ruppert, David
Contributor(s): Wand, M. P
| Carroll, R. J
Material type: 



Item type | Current location | Item location | Collection | Call number | Status | Date due | Barcode |
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Books | Vikram Sarabhai Library General Stacks | Slot 1428 (0 Floor, East Wing) | Non-fiction | 519.536 R8S3 (Browse shelf) | Available | 195962 |
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519.536 M2S8 Statistical regression and classification: from linear models to machine learning | 519.536 M6I6 Introduction to linear regression analysis | 519.536 R4R6 Robust nonlinear regression: with application using R | 519.536 R8S3 Semiparametric Regression | 519.536 T2M2 The manga guide to regression analysis | 519.536 Y6H2 Handbook of regression methods | 519.53602 8553 S8F5 Flexible regression and smoothing: using GAMLSS in R |
Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The 2003 book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.
https://www.cambridge.org/core/books/semiparametric-regression/02FC9A9435232CA67532B4D31874412C#fndtn-information
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