TY - JOUR
T1 - Variable selection in a partially linear proportional hazards model with a diverging dimensionality
AU - Hu, Yuao
AU - Lian, Heng
PY - 2013/1
Y1 - 2013/1
N2 - We consider the problem of simultaneous variable selection and estimation in partially linear proportional hazards models when the number of covariates in the linear part diverges with the sample size. We apply the smoothly clipped absolute deviation (SCAD) penalty to select the significant covariates in the linear part. Some simulations and a real data set are presented. © 2012 Elsevier B.V.
AB - We consider the problem of simultaneous variable selection and estimation in partially linear proportional hazards models when the number of covariates in the linear part diverges with the sample size. We apply the smoothly clipped absolute deviation (SCAD) penalty to select the significant covariates in the linear part. Some simulations and a real data set are presented. © 2012 Elsevier B.V.
KW - Akaike information criterion (AIC)
KW - Bayesian information criterion (BIC)
KW - Cross-validation
KW - Partial likelihood
KW - SCAD
UR - http://www.scopus.com/inward/record.url?scp=84866544176&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84866544176&origin=recordpage
U2 - 10.1016/j.spl.2012.08.024
DO - 10.1016/j.spl.2012.08.024
M3 - RGC 21 - Publication in refereed journal
SN - 0167-7152
VL - 83
SP - 61
EP - 69
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
IS - 1
ER -