Quantile regression is a powerful complement to the usual mean regression and becomes increasingly popular due to its desirable properties. In longitudinal studies, it is necessary to consider the intra-subject correlation among repeated measures over time to improve the estimation efficiency. In this paper, we focus on longitudinal single-index models. Firstly, we apply the modified Cholesky decomposition to parameterize the intra-subject covariance matrix and develop a regression approach to estimate the parameters of the covariance matrix. Secondly, we propose efficient quantile estimating equations for the index coefficients and the link function based on the estimated covariance matrix. Since the proposed estimating equations include a discrete indicator function, we propose smoothed estimating equations for fast and accurate computation of the index coefficients, as well as their asymptotic covariances. Thirdly, we establish the asymptotic properties of the proposed estimators. Finally, simulation studies and a real data analysis have illustrated the efficiency of the proposed approach.
The micropolar theory for fluids is adopted to probe the effect of the microstructure and microrotation on lubrication features in thin film lubrication. Micropolarity will give rise to an increase in the equivalent viscosity that subsequently leads to a better lubrication. The effective viscosity grown with micro polarity is very close to that of experiment in a preceding work. 相似文献
Varying index coefficient models (VICMs) proposed by Ma and Song (J Am Stat Assoc, 2014. doi:10.1080/01621459.2014.903185) are a new class of semiparametric models, which encompass most of the existing semiparametric models. So far, only the profile least squares method and local linear fitting were developed for the VICM, which are very sensitive to the outliers and will lose efficiency for the heavy tailed error distributions. In this paper, we propose an efficient and robust estimation procedure for the VICM based on modal regression which depends on a bandwidth. We establish the consistency and asymptotic normality of proposed estimators for index coefficients by utilizing profile spline modal regression method. The oracle property of estimators for the nonparametric functions is also established by utilizing a two-step spline backfitted local linear modal regression approach. In addition, we discuss the bandwidth selection for achieving better robustness and efficiency and propose a modified expectation–maximization-type algorithm for the proposed estimation procedure. Finally, simulation studies and a real data analysis are carried out to assess the finite sample performance of the proposed method. 相似文献
In this paper, the particle movements in a sessile droplet induced by standing surface acoustic waves (SSAWs) are studied. Tritoroidal particle rings are formed under the interaction of acoustic field and electric field. The experimental results demonstrate that the electric field plays an important role in patterning nanoparticles. The electric field can define the droplet shape due to electrowetting. When the droplet approximates a hemisphere, the acoustic radiation force induced by SSAWs drives the particles to form tritoroidal particle rings. When the droplet approximates a convex plate, the drag force induced by acoustic steaming drives the particle to move. The results will be useful for better understanding the nanoparticle movements in a sessile droplet, which is important to explain the mechanism that SSAWs enhance reaction and crystallization in droplet. 相似文献