LINEARIZATION OF RANDOMLY WEIGHTED EMPIRICALS UNDER LONG RANGE DEPENDENCE WITH APPLICATIONS TO NONLINEAR REGRESSION QUANTILES
长程依赖下随机加权经验过程的线性化及非线性回归分位数应用
This paper discusses some asymptotic uniform linearity results of randomly weighted empirical processes based on long range dependent random variables. These results are subsequently used to linearize nonlinear regression quantiles in a nonlinear regression model with long range dependent errors, where the design variables can be either random or nonrandom. These, in turn, yield the limiting behavior of the nonlinear regression quantiles. As a corollary, we obtain the…