1 |
Zhao J, Leng C, Li L, and Wang H (2013). High-dimensional influence measure, The Annals of Statistics, 41, 2639-2667.
DOI
|
2 |
BaeW, Noh S, and Kim C (2017). Case influence diagnostics for the significance of the linear regres-sion model, Communications for Statistical Applications and Methods, 24, 155-162.
|
3 |
Box GEP and Cox DR (1964). An analysis of transformations. Journal of the Royal Statistical Society, Series B, 26, 211-252.
|
4 |
Cook RD (1977). Detection of influential observation in linear regression, Technometrics, 19, 15-18.
|
5 |
Hoerl AE and Kennard RW (1970). Ridge regression: biased estimation for nonorthogonal problems, Technometrics, 12, 55-67.
DOI
|
6 |
Jang DH and Anderson-Cook CM (2017). Influence plots for LASSO, Quality and Reliability in Engineering International, 33, 1317-1326.
DOI
|
7 |
Kim C, Lee J, Yang H, and Bae W (2015). Case influence diagnostics in the lasso regression. Journal of the Korean Statistical Society, 44, 271-279.
DOI
|
8 |
Kim J and Lee S (2017). A convenient approach for penalty parameter selection in robust lasso regression, Communications for Statistical Applications and Methods, 24, 651-662.
DOI
|
9 |
Lu T, Pan Y, Kao SY, Kohane I, and Chan J (2004). Gene regulation and DNA damage in the ageing human brain, Nature, 429, 883-891.
DOI
|
10 |
Tibshirani R (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society, Series B, 58, 267-288.
|