Bernstein Inequality for Multivariate Point Processes

来源 :上海交通大学 | 被引量 : 0次 | 上传用户:cywxp
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
  At first we review some classical results on Bernstein type inequalities and latest progress.Then we introduce our new results on a Bernstein type concentration inequality for multivariate point processes and a uniform exponential inequality for multivariate point processes by generic chaining method.
其他文献
Nonignorable nonresponse presents a great challenge in statistical analysis since the nonresponse mechanism/propensity depends on missing data and it is often not identifiable without any further assu
In analyzing longitudinal data,within-subject correlations are a major factor that affects statistical efficiency.Working with a partially linear model for longitudinal data,we consider a subject-wise
We study the estimation of high dimensional minimum variance portfolio(MVP).Two settings are considered: the low frequency setting where returns are modeled as i.i.d.,and the high frequency setting wh
In this paper,we consider testing regression coefficients in high dimensional generalized linear models.By modifying Goeman et al.(2011)s test statistic for large,fixed dimensional settings,we propose
We introduce a nonparametric graphical model whose observations on vertices are functions.Many modern applications,such as electroencephalogram and functional magnetic resonance imaging(fMRI),produce
For familial disease,one main task is to estimate the probability distribution of genetic mutation in carrier and non-carrier groups using pedigrees history information.
Next-generation sequencing studies on cancer somatic mutations have discovered that driver mutations tend to appear in most tumor samples,but they barely overlap in any single tumor sample,presumably
We considered testing for two-sample covariance matrices of high dimensional populations.We formulate a multiple test procedure by comparing the super-diagonals of the covariance matrices.
Complex networks,which describe a variety of systems found in nature and society,have attracted a tremendous amount of attention in the past decade among physicists and mathematicians.Numerous complex
We consider the multivariate process monitoring when a group of variables with strong correlation tends to suffer from abnormal changes simultaneously.Such a problem arises naturally in many practical