The exposome represents the totality of life course environmental exposures (including
lifestyle and other non-genetic factors), from the prenatal period onwards. This holistic …

Partially linear additive quantile regression in ultra-high dimension Page 1 The Annals of
Statistics 2016, Vol. 44, No. 1, 288–317 DOI: 10.1214/15-AOS1367 © Institute of …

We continue our review of issues related to measurement error and misclassification in
epidemiology. We further describe methods of adjusting for biased estimation caused by …

Semiparametric additive partial linear models, containing both linear and nonlinear additive
components, are more flexible compared to linear models, and they are more efficient …

This paper proposes a new penalized time-varying model averaging method to determine
optimal time-varying combination weights for candidate models, which avoids over-fitting …

Regression with the lasso penalty is a popular tool for performing dimension reduction when
the number of covariates is large. In many applications of the lasso, like in genomics …

This paper focuses on the variable selections for semiparametric varying coefficient partially
linear models when the covariates in the parametric and nonparametric components are all …

This paper investigates variable selection in the spatial autoregressive model with
independent and identical distributed errors. A penalized quasi-maximum likelihood method …

Measurement error data or errors-in-variable data are often collected in many studies.
Natural criterion functions are often unavailable for general functional measurement error …

Spatial dependent data frequently occur in spatial econometrics and endemiology. In this
work, we propose a class of penalized robust regression estimators based on exponential …