The Meyers Inequality for Symmetric Jump Processes in Metric Measure Spaces

来源 :上海交通大学 | 被引量 : 0次 | 上传用户:kakingka
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
  The Lp regularity with some p > 2 for the solution to the Poisson type equation with respect to non-local operators,including the generator of = symmetric jump processes,is established in the metric measure space,which is achieved by generalizing the Meyers inequality on elliptic operators in the Euclidean space.As an application,the strong stability for the semigroup corresponding to the non-local operator,as well as the heat kernel,is proved.
其他文献
In general,the cluster analysis on the climatological data is useful method that the climate characteristic of South Korea is analyzed by clusters.
We develop econometric tools to study integrated volatility with potentially time-dependent microstructure noise in high-frequency data.
Suppose we are interested in a causal effect that is confounded by an unobserved variable.Suppose however one has available negative control outcomes that are not causally affected by the treatment,an
Hamiltonian Monte Carlo(HMC)has become routinely used for sampling from posterior distributions.Its extension Riemann manifold HMC(RMHMC)modifies the proposal kernel through distortion of local distan
In this paper we present an innovative non-parametric Bayesian approach to estimate and predict individual patient longitudinal biomarker distributions.
Next generation sequencing(NGS)data contain measurement errors.Normalizing NGS data is challenging and crucial.We propose to normalize the NGS gene expression profiles via binning and density estimati
Here we introduce a new analytical method for testing the hypothesis that the medians of two distributions are equal or within some range of one another,given independent draws from each,or that the m
Berliner(1991)identified a number of difficulties in using the likelihood function within the Bayesian paradigm for state estimation of chaotic systems.Even when the equations of the system are given,
Complex large-scale studies,such as those related to microarray and quantitative trait loci,often involve testing multiple hierarchically ordered hypotheses.
This paper studies minimax rates of nonparametric classification under the framework of sparse support vector machine(SVM)with multiple kernels.
会议