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Generalized additive models for medical research
Generalized additive models medical research
2015/8/21
This article reviews flexible statistical methods that are useful for characterizing the effect of potential prognostic factors on disease endpoints. Applications to survival models and binary outcome...
A Distributed Algorithm for Fitting Generalized Additive Models
Convex optimization Distributed optimization Generalized additive models
2015/7/9
Generalized additive models are an effective regression tool, popular in the statistics literature, that provide an automatic extension of traditional linear models to nonlinear systems. We pres...
Bayesian Functional Generalized Additive Models with Sparsely Observed Covariates
auction data functional data analysis functional regression linear mixed models measurement error MCMC penalized splines variational inference
2013/6/14
The functional generalized additive model (FGAM) was recently proposed in McLean et al. (2012) as a more flexible alternative to the common functional linear model (FLM) for regressing a scalar on fun...
Asymptotics for penalized splines in generalized additive models
Asymptotic normality B-spline Generalized additive model Mixed model Pe-nalized spline
2012/9/17
This paper discusses asymptotic theory for penalized spline estimators in generalized additive models. The purpose of this paper is to establish the asymptotic bias and variance as well as the asympto...
PAC-Bayesian Estimation and Prediction in Sparse Additive Models
Additive models sparsity regression estimation PAC-Bayesian bounds oracle inequality MCMC stochastic search.
2012/9/17
The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption (p nparadigm).A PAC-Bayesian strategy is investigated, delivering oracle inequaliti...
Two-step estimation of high dimensional additive models
additive model group Lasso penalized least squares.
2012/9/19
This paper investigates the two-step estimation of a high dimensional additive regression model, in which the number of nonparametric additive components is potentially larger than the sample size but...
Estimation in additive models with highly or nonhighly correlated covariates
Additive model backfitting local linear smoothing normalizatio
2010/10/14
Motivated by normalizing DNA microarray data and by predicting the interest rates, we explore nonparametric estimation of additive models with highly correlated covariates. We introduce two novel appr...
A Note on The Backfitting Estimation of Additive Models
additive model backfitting algorithm convergence of algorithm kernelsmoothing
2010/3/18
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...
A simple smooth backfitting method for additive models
Backfitting nonparametric regression local linear smoothing
2010/4/26
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
...