Variable selection in high-dimensional partly linear additive models
Semiparametric models are particularly useful for high-dimensional regression problems. In this paper, we focus on partly linear additive models with a large number of predictors (can be larger than the sample size) and consider model estimation and variable selection based on polynomial spline expa...
محفوظ في:
المؤلف الرئيسي: | Lian, Heng |
---|---|
مؤلفون آخرون: | School of Physical and Mathematical Sciences |
التنسيق: | مقال |
اللغة: | English |
منشور في: |
2013
|
الموضوعات: | |
الوصول للمادة أونلاين: | https://hdl.handle.net/10356/97695 http://hdl.handle.net/10220/17096 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
المؤسسة: | Nanyang Technological University |
اللغة: | English |
مواد مشابهة
-
Estimation by polynomial splines with variable selection in additive Cox models
بواسطة: Zhang, Shangli, وآخرون
منشور في: (2013) -
SCAD-penalised generalised additive models with non-polynomial dimensionality
بواسطة: Li, Gaorong, وآخرون
منشور في: (2013) -
Generalized additive partial linear models with high-dimensional covariates
بواسطة: Lian, Heng, وآخرون
منشور في: (2014) -
Variable selection for high-dimensional varying coefficient partially linear models via nonconcave penalty
بواسطة: Hong, Zhaoping, وآخرون
منشور في: (2013) -
Generalized additive partial linear models for clustered data with diverging number of covariates using gee
بواسطة: Wang, Lan, وآخرون
منشور في: (2014)