Smooth backfitting in generalized additive models
نویسندگان
چکیده
منابع مشابه
Smooth Backfitting in Generalized Additive Models
Generalized additive models have been popular among statisticians and data analysts in multivariate nonparametric regression with non-Gaussian responses including binary and count data. In this paper, a new likelihood approach for fitting generalized additive models is proposed. It aims to maximize a smoothed likelihood. The additive functions are estimated by solving a system of nonlinear inte...
متن کاملBandwidth Selection for Smooth Backfitting in Additive Models
The smooth backfitting introduced byMammen, Linton and Nielsen [Ann. Statist. 27 (1999) 1443–1490] is a promising technique to fit additive regression models and is known to achieve the oracle efficiency bound. In this paper, we propose and discuss three fully automated bandwidth selection methods for smooth backfitting in additive models. The first one is a penalized least squares approach whi...
متن کاملA Simple Smooth Backfitting Method for Additive Models
In this paper a new smooth backfitting estimate is proposed for additive regression models. The estimate has the simple structure of Nadaraya–Watson smooth backfitting but at the same time achieves the oracle property of local linear smooth backfitting. Each component is estimated with the same asymptotic accuracy as if the other components were known. 1. Introduction. In additive models it is ...
متن کاملNonparametric Lag Selection for Additive Models Based on the Smooth Backfitting Estimator
This paper proposes a nonparametric FPE-like procedure based on the smooth backfitting estimator when the additive structure is a priori known. This procedure can be expected to perform well because of its well-known finite sample performance of the smooth backfitting estimator. Consistency of our procedure is established under very general conditions, including heteroskedasticity.
متن کاملA Note on The Backfitting Estimation of Additive Models
The additive model is one of the most popular semiparametric models. The backfitting estimation (Buja, Hastie and Tibshirani, 1989, Ann. Statist.) for the model is intuitively easy to understand and theoretically most efficient (Opsomer and Ruppert, 1997, Ann. Statist.); its implementation is equivalent to solving simple linear equations. However, convergence of the algorithm is very difficult ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2008
ISSN: 0090-5364
DOI: 10.1214/009053607000000596