|
|
| |
| Model Selection Consistency of Lasso for Empirical Data |
| |
Citation： |
Yuehan YANG,Hu YANG.Model Selection Consistency of Lasso for Empirical Data[J].Chinese Annals of Mathematics B,2018,39(4):607~620 |
| Page view： 769
Net amount： 693 |
Authors： |
Yuehan YANG; Hu YANG |
Foundation： |
This work was supported by the
National Natural Science Foundation of China (No. 11671059) and the Fundamental Research Funds for the Central Universities. |
|
|
| Abstract： |
Large-scale empirical data, the sample size and the dimension are
high, often exhibit various characteristics. For example, the noise
term follows unknown distributions or the model is very sparse that
the number of critical variables is fixed while dimensionality grows
with $n$. The authors consider the model selection problem of lasso
for this kind of data. The authors investigate both theoretical
guarantees and simulations, and show that the lasso is robust for
various kinds of data. |
Keywords： |
Lasso, Model selection, Empirical data |
Classification： |
62J05, 62J07 |
|
|
Download PDF Full-Text
|
|
|
|
