Censored regression ("Tobit") models have been in common use, and their linear hypothesis testings have been widely studied. However, the critical values of these tests are usually related to quantities of a...Censored regression ("Tobit") models have been in common use, and their linear hypothesis testings have been widely studied. However, the critical values of these tests are usually related to quantities of an unknown error distribution and estimators of nuisance parameters. In this paper, we propose a randomly weighting test statistic and take its conditional distribution as an approximation to null distribution of the test statistic. It is shown that, under both the null and local alternative hypotheses, conditionally asymptotic distribution of the randomly weighting test statistic is the same as the null distribution of the test statistic. Therefore, the critical values of the test statistic can be obtained by randomly weighting method without estimating the nuisance parameters. At the same time, we also achieve the weak consistency and asymptotic normality of the randomly weighting least absolute deviation estimate in censored regression model. Simulation studies illustrate that the per-formance of our proposed resampling test method is better than that of central chi-square distribution under the null hypothesis.展开更多
We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon- cave regul...We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon- cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of o（√n）, where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.展开更多
无线传感器网络存在易遭受恶意节点攻击而导致能量浪费和数据丢失等问题,为解决该问题,提出ETM-LEACH(energy and trust models based LEACH)算法。通过均衡网络能耗计算动态最优簇首数,引入能量判决因子、节点密度因子、节点信任因子...无线传感器网络存在易遭受恶意节点攻击而导致能量浪费和数据丢失等问题,为解决该问题,提出ETM-LEACH(energy and trust models based LEACH)算法。通过均衡网络能耗计算动态最优簇首数,引入能量判决因子、节点密度因子、节点信任因子改进选举簇首的阈值计算公式。加入绝对偏差过滤掉能量较低节点,采用信任模型引入多种状态信息计算直接信任值和间接信任值,筛选高可信节点。仿真结果表明,与现有协议相比,该协议能够有效降低节点能耗,优化网络部署,提高网络的安全性和可靠性。展开更多
基金supported by National Natural Science Foundation of China (Grant No. 10471136)PhD Program Foundation of the Ministry of Education of ChinaSpecial Foundations of the Chinese Academy of Sciences and University of Science and Technology of China
文摘Censored regression ("Tobit") models have been in common use, and their linear hypothesis testings have been widely studied. However, the critical values of these tests are usually related to quantities of an unknown error distribution and estimators of nuisance parameters. In this paper, we propose a randomly weighting test statistic and take its conditional distribution as an approximation to null distribution of the test statistic. It is shown that, under both the null and local alternative hypotheses, conditionally asymptotic distribution of the randomly weighting test statistic is the same as the null distribution of the test statistic. Therefore, the critical values of the test statistic can be obtained by randomly weighting method without estimating the nuisance parameters. At the same time, we also achieve the weak consistency and asymptotic normality of the randomly weighting least absolute deviation estimate in censored regression model. Simulation studies illustrate that the per-formance of our proposed resampling test method is better than that of central chi-square distribution under the null hypothesis.
基金supported by National Institute on Drug Abuse(Grant Nos.R21-DA024260 and P50-DA10075)National Natural Science Foundation of China(Grant Nos.11071077,11371236,11028103,11071022 and 11028103)+2 种基金Innovation Program of Shanghai Municipal Education CommissionPujiang Project of Science and Technology Commission of Shanghai Municipality(Grant No.12PJ1403200)Program for New Century Excellent Talents,Ministry of Education of China(Grant No.NCET-12-0901)
文摘We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon- cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of o（√n）, where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.
文摘无线传感器网络存在易遭受恶意节点攻击而导致能量浪费和数据丢失等问题,为解决该问题,提出ETM-LEACH(energy and trust models based LEACH)算法。通过均衡网络能耗计算动态最优簇首数,引入能量判决因子、节点密度因子、节点信任因子改进选举簇首的阈值计算公式。加入绝对偏差过滤掉能量较低节点,采用信任模型引入多种状态信息计算直接信任值和间接信任值,筛选高可信节点。仿真结果表明,与现有协议相比,该协议能够有效降低节点能耗,优化网络部署,提高网络的安全性和可靠性。
