Name: Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach (Chapman & Hall (en Inglés)
SKU: 51003224
Price: 278.88 USD
Availability: InStock
Author: P. J. Green

portada Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach (Chapman & Hall (en Inglés)

Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach (Chapman & Hall (en Inglés)

Formato

Libro Físico

Editorial

Taylor & Francis Ltd

Autor

P. J. Green

Categoría

Libros de Textos

Año

1993

Idioma

Inglés

N° páginas

184

Encuadernación

Tapa Dura

ISBN13

9780412300400

N° edición

Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach (Chapman & Hall (en Inglés)

P. J. Green (Autor) · Taylor & Francis Ltd · Tapa Dura

Libro Nuevo Importado

Envío: 18 a 25 días háb.

$ 557.76$ 278.88

-50%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 10 unidades

$ 278.88

Llega entre el 17 Sep y el 30 Sep a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach (Chapman & Hall (en Inglés)"

In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method allows parametric assumptions to be realized in regression problems, in those approached by generalized linear modelling, and in many other contexts.The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus.This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.