本文提出围绕一个非参数的定位功能,能够检测到一般的非参数的选择条件分布对称测试。该测试是开发一个通用串行依赖的背景下,创新的地方可能会出现一个未知的高阶序列依赖结构。检验统计量是一种功能性的非参数的残差和解释变量的联合经验分布,其可以检测非参数替代会聚到空的参数速率根-n的。临界值估计用自举技术容易实现的协助下,将所得测试的有效性的规律性的条件下正式有道理的。蒙特卡洛研究探讨了测试的有限样本性质。我们还调查损失是否超过给定的使用我们的测试方法股市的可用信息收益的可能性较大。以下是在职研究生讲座原文。
Testing Symmetry of a Nonparametric Conditional Distribution
This article proposes tests of symmetry of conditional distributions around a nonparametric location function able to detect general non-parametric alternatives. The test is developed in a general serial dependence context, where innovations may exhibit an unknown higher order serial dependence structure. The test statistic is a functional of the joint empirical distribution of non-parametric residuals and explanatory variables, which can detect non-parametric alternatives converging to the null at the parametric rate root-n. Critical values are estimated with the assistance of a bootstrap technique easy to implement, and the validity of the resulting test is formally justified under the regularity conditions. A Monte Carlo study examines the finite sample properties of the test. We also investigate whether losses are more likely than gains given the available information in stock markets using our testing approach.
在职研究生报名条件是:
1、在教学、科研、专门技术、管理等方面做出成绩。2、获得学士学位后工作三年以上(含三年)或者虽无学士学位但已获硕士或博士学位者,对已获得的学士、硕士或博士学位为国(境)外的,其获得的国(境)外学位需经教育部留学服务中心认证。3、申请学科与所学专业相同或相近。完成学业后可以获得结业证,满足条件的考生可以参加全国同等学习能力人员申请硕士学位统一考试,每年5月进行全国联考,3月在学位网报名,考生在规定年限内通过考试达到及格线即可,然后进入论文写作和答辩流程,通过以后获取硕士学位。