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[null,null,"Autore",null,"Harezlak Jaroslaw"]
[null,null,"Titolo",null,"Semiparametric Regression with R / / by Jaroslaw Harezlak, David Ruppert, Matt P. Wand"]
[null,null,"Pubbl/distr/stampa",null,"New York, NY : , : Springer New York : , : Imprint : Springer, , 2018"]
[null,null,"ISBN",null,"9781493988532"]
[{"$nulls":4},"1493988530"]
[null,null,"Edizione",null,"[1st ed. 2018.]"]
[null,null,"Descrizione fisica",null,"1 online resource (341 pages)"]
[null,null,"Collana",null,"Use R!, , 2197-5744"]
[null,null,"Disciplina",null,"519.536"]
[null,null,"Soggetti",null,"Statistics"]
[{"$nulls":4},"Biometry"]
[{"$nulls":4},"Statistical Theory and Methods"]
[{"$nulls":4},"Biostatistics"]
[{"$nulls":4},"Statistics in Business, Management, Economics, Finance, Insurance"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Introduction -- Penalized Splines -- Generalized Additive Models -- Semiparametric Regression Analysis of Grouped Data -- Bivariate Function Extensions -- Selection of Additional Topics.-Index."]
[null,null,null,"Sommario/riassunto","This easy-to-follow applied book expands upon the authors’ prior work on semiparametric regression to include the use of R software. In 2003, authors Ruppert and Wand co-wrote Semiparametric Regression with R.J. Carroll, which introduced the techniques and benefits of semiparametric regression in a concise and user-friendly fashion. Fifteen years later, semiparametric regression is applied widely, powerful new methodology is continually being developed, and advances in the R computing environment make it easier than ever before to carry out analyses. Semiparametric Regression with R introduces the basic concepts of semiparametric regression with a focus on applications and R software. This volume features case studies from environmental, economic, financial, and other fields. The examples and corresponding code can be used or adapted to apply semiparametric regression to a wide range of problems. It contains more than fifty exercises, and the accompanying HRW package contains all datasets and scripts used in the book, as well as some useful R functions. This book is suitable as a textbook for advanced undergraduates and graduate students, as well as a guide for "]
[{"$nulls":4},"statistically-oriented practitioners, and could be used in conjunction with Semiparametric Regression. Readers are assumed to have a basic knowledge of R and some exposure to linear models. For the underpinning principles, calculus-based probability, statistics, and linear algebra are desirable."]