Penalized methods for bi-level variable selection
نویسندگان
چکیده
منابع مشابه
Penalized methods for bi-level variable selection.
In many applications, covariates possess a grouping structure that can be incorporated into the analysis to select important groups as well as important members of those groups. This work focuses on the incorporation of grouping structure into penalized regression. We investigate the previously proposed group lasso and group bridge penalties as well as a novel method, group MCP, introducing a f...
متن کاملRegularized methods for high-dimensional and bi-level variable selection
Many traditional approaches to statistical analysis cease to be useful when the number of variables is large in comparison with the sample size. Penalized regression methods have proved to be an attractive approach, both theoretically and empirically, for dealing with these problems. This thesis focuses on the development of penalized regression methods for high-dimensional variable selection. ...
متن کاملThe group exponential lasso for bi-level variable selection.
In many applications, covariates possess a grouping structure that can be incorporated into the analysis to select important groups as well as important members of those groups. One important example arises in genetic association studies, where genes may have several variants capable of contributing to disease. An ideal penalized regression approach would select variables by balancing both the ...
متن کاملVariable Selection via Penalized Likelihood
Variable selection is vital to statistical data analyses. Many of procedures in use are ad hoc stepwise selection procedures, which are computationally expensive and ignore stochastic errors in the variable selection process of previous steps. An automatic and simultaneous variable selection procedure can be obtained by using a penalized likelihood method. In traditional linear models, the best...
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: Statistics and Its Interface
سال: 2009
ISSN: 1938-7989,1938-7997
DOI: 10.4310/sii.2009.v2.n3.a10