We report the preparation of ZnO quantum dot hybrid luminescent resists for nanoimprint lithography. Photoluminescence spectra indicate that ZnO QDs@AMONIL have a significant increase in the luminescent intensity, an obvious blue-shift of emission peak and the Stoke's shift, revealing that ZnO...

In Build-Operate-Transfer (BOT) infrastructure projects, host governments often provide subsidies, guarantees or alternative forms of support as incentives to attract private sector participation. A guaranteed level of minimum revenue, for example, can be specially designed to alleviate the...

A novel and robust method is proposed by combining the idea of the modal regression estimation (Yao et al., 2012) and spline based shrinkage estimation method (Lian, 2012). The newly proposed method can simultaneously estimate and separate constant coefficients from varying coefficients and its...

In this paper, we consider how to yield a robust empirical likelihood estimation for regression models. After introducing modal regression, we propose a novel empirical likelihood method based on modal regression estimation equations, which has the merits of both robustness and high inference...

Partial linear single-index model (PLSIM) is a flexible and applicable model when investigating the underlying relationship between the response and the multivariate covariates. Most previous studies on PLSIM concentrated on mean regression, based on least square or likelihood approach. In...

The varying coefficient model (VCM) is an important generalization of the linear regression model and many existing estimation procedures for VCM were built on <italic>L</italic> ₂ loss, which is popular for its mathematical beauty but is not robust to non-normal errors and outliers. In this paper, we address...

The group Lasso is a penalized regression method, used in regression problems where the covariates are partitioned into groups to promote sparsity at the group level [27]. Quantile group Lasso, a natural extension of quantile Lasso [25], is a good alternative when the data has group information...

In this paper, we propose a new full iteration estimation method for quantile regression (QR) of the single-index model (SIM). The asymptotic properties of the proposed estimator are derived. Furthermore, we propose a variable selection procedure for the QR of SIM by combining the estimation...

Semiparametric partially linear varying coefficient models (SPLVCM) are frequently used in statistical modeling. With high-dimensional covariates both in parametric and nonparametric part for SPLVCM, sparse modeling is often considered in practice. In this paper, we propose a new estimation and...

The beta regression models are commonly used by practitioners to model variables that assume values in the standard unit interval (0, 1). In this paper, we consider the issue of variable selection for beta regression models with varying dispersion (VBRM), in which both the mean and the...