Variable Selection in Kernel Regression Using Measurement Error Selection Likelihoods
نویسندگان
چکیده
منابع مشابه
Bayesian Approximate Kernel Regression with Variable Selection
Nonlinear kernel regression models are often used in statistics and machine learning due to greater accuracy than linear models. Variable selection for kernel regression models is a challenge partly because, unlike the linear regression setting, there is no clear concept of an effect size for regression coefficients. In this paper, we propose a novel framework that provides an analog of the eff...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2017
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2016.1222287