Analysis on Dynamic Dielectric Recovery and Statistical Property of Vacuum Circuit-Breakers with Multi-Breaks

Based on the dynamic dielectric recovery process in the vacuum gaps in series, investigations were made on post-arc insulation state in double and multi-breaks operation in high voltage power system. From the research on the breakdown weak points in high voltage vacuum gaps, their turnout and distribution, some theoretic work were made to set up the models for describing the statistical property of multi-breaks vacuum circuit-breakers' breakdown and post-arc re-strike, which can be used for explaining the mechanism of the improvement in the breaking capacity of multi-breaks units compared with that of single-break ones which have the same equivalent gap length. The advantages of vacuum breakers with multi-breaks are proposed.

Finite sample breakdown point of Tukey＇s halfspace median

Tukey's halfspace median(HM), servicing as the multivariate counterpart of the univariate median,has been introduced and extensively studied in the literature. It is supposed and expected to preserve robustness property(the most outstanding property) of the univariate median. One of prevalent quantitative assessments of robustness is finite sample breakdown point(FSBP). Indeed, the FSBP of many multivariate medians have been identified, except for the most prevailing one—the Tukey's halfspace median. This paper presents a precise result on FSBP for Tukey's halfspace median. The result here depicts the complete prospect of the global robustness of HM in the finite sample practical scenario, revealing the dimension effect on the breakdown point robustness and complimenting the existing asymptotic breakdown point result.

The Limit of Finite Sample Breakdown Point of Tukey’s Halfspace Median for General Data

Under special conditions on data set and underlying distribution, the limit of finite sample breakdown point of Tukey＇s halfspace median （1） has been obtained in the literature. In this paper, we establish the result under weaker assumptions imposed on underlying distribution （weak smoothness） and on data set （not necessary in general position）. The refined representation of Tukey＇s sample depth regions for data set not necessary in general position is also obtained, as a by-product of our derivation.

ON WEIGHTED RANDOMLY TRIMMED MEANS

A class of robust location estimators called weighted randomly trimmed means are introduced and not only their consistency and asymptotic normality are proved, but their influence functions, asymptotic variances and breakdown points are also derived. They possess the same breakdown points as the median, and some of them own higher asymptotic relative efficiencies at the heavy-tailed distributions than some other well-known location estimators; whereas the trimmed means, Winsorized means and Huber＇s M-estimator possess higher asymptotic relative efficiencies at the light-tailed distributions, in which Huber＇s M-estimator is the most robust.

A note on constrained M-estimation and its recursive analog in multivariate linear regression models

In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in a general multivariate linear regression model is considered. Since the constrained M-estimation is not easy to compute, an up-dating recursion procedure is proposed to simplify the computation of the estimators when a new observation is obtained. We show that, under mild conditions, the recursion estimates are strongly consistent. In addition, the asymptotic normality of the recursive constrained M-estimators of regression coefficients is established. A Monte Carlo simulation study of the recursion estimates is also provided. Besides, robustness and asymptotic behavior of constrained M-estimators are briefly discussed.

LARGE SAMPLE AND ROBUST PROPERTIES OF L^2-MEDIAN

As a competitive depth, L^2-depth is modified from L^2-depth. Its induced median is called L^2-median. Basic properties of the median and its sample version are provided. Especially, the strong consistency of sample median is gained under weaker condition. Robustness of the median and its sample version is discussed. Besides ease of computation, it is shown that L^2-median has both good large-sample and robust properties. Simulation studies are also given to compare the breakdown point of L^2-median with that of other depth-induced medians.