期刊： METRIKA, ; ()
In recent years, there has been great interest in using network structure to improve classic statistical models in cases where individuals are depende......
期刊： METRIKA, ; ()
The use of the first two moments of the truncated multivariate Student-t distribution has attracted increasing attention from a wide range of applicat......
期刊： METRIKA, ; ()
In this paper, we focus on the estimation and inference in partially nonlinear additive model on which few research was conducted to our best knowledg......
期刊： METRIKA, ; ()
The validation of diagnostic test meta-analysis is often threatened by publication bias, which can be commonly characterized by the Copas selection mo......
In this paper, we investigate two inequalities based on majorization for two random vectors with different Gaussian marginals and the same underlying ......
The paper concerns the regularized quantile regression for ultrahigh-dimensional data with responses missing not at random. The propensity score is sp......
Fractional factorial designs are widely used because of their various merits. Foldover or level permutation are usually used to construct optimal frac......
We investigate kernel estimates in the functional nonparametric regression model when both the response and the explanatory variable (the covariate) a......
This paper considers constructions of optimal designs for heteroscedastic polynomial measurement error models. Corresponding approximate design theory......
This paper is concerned with feature screening for the ultrahigh dimensional discriminant analysis. A new feature screening procedure based on the con......
The Lasso approach is widely adopted for screening and estimating active effects in sparse linear models with quantitative factors. Many design scheme......
It becomes increasingly common to incorporate the predictors' grouping knowledge into dimension reduction techniques. In this article, we establish a ......
We consider the variable selection problem in a sparse logistical regression model. Inspired by the square-root Lasso, we develop a weighted score Las......
In this paper, we develop statistical inference procedures for functional quadratic quantile regression model in which the response is a scalar and th......
This paper presents the nonparametric quantile regression estimation for the regression function operator when the functional data with the responses ......
