Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The use of these nonparametric functions with parametric techniques can yield very powerful data analysis tools. Local polynomial modeling and its applications provides an up-to-date picture on state-of-the-art nonparametric regression techniques. The emphasis of the book is on methodologies rather than on theory, with a particular focus on applications of nonparametric techniques to various statistical problems. High-dimensional data-analytic tools are presented, and the book includes a variety of examples. This will be a valuable reference for research and applied statisticians, and will serve as a textbook for graduate students and others interested in nonparametric regression.
Betaal eenvoudig met kaart, Klarna, Apple Pay of Google Pay. Niet tevreden? Je hebt altijd 14 dagen bedenktijd. Lees meer in onze voorwaarden. Heb je vragen, mail ons dan via hello@memmo.org.
Memmo maakt studeren makkelijker – waar je ook bent ter wereld. Wij brengen je cursusboeken en slimme studietools samen op één plek: samenvattingen, quizzen, podcasts en flashcards. En Ted, je studievriend die antwoord geeft op alles wat je je afvraagt. Meer dan 50.000 studenten studeren hier al – gebouwd om je sneller te laten leren en minder stress te geven.
Misschien vind je dit ook leuk
Koop het boek0