• 不 限
  • 期刊论文
  • 硕博论文
  • 会议论文
  • 报 纸
  • 英文论文
  2. 您的位置
  3. 首页
  4. 会议论文
  5. Background rates of swarm earthquakes that are synchronized with volumetric strain changes:An Applic

Background rates of swarm earthquakes that are synchronized with volumetric strain changes:An Applic

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：liqixuexue
【摘 要】
：
Off the east coast of the Izu Peninsula in Japan is a submarine volcanic region.There earthquake swarms have been observed many times caused by magma intrusions.
【作 者】
：
Takao Kumazawa Yosihiko Ogata Kazuhiro Kimura Kenji Maeda Akio Kobayashi 
【机 构】
：
The Institute of Statistical Mathematics,Japan Th
【出 处】
：
上海交通大学
【发表日期】
：
2016年4期
【关键词】
：
ETAS model Bayesian Smoothing Earthquake Swarms 
下载到本地 , 更方便阅读
下载此文 赞助VIP
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
　　Off the east coast of the Izu Peninsula in Japan is a submarine volcanic region.There earthquake swarms have been observed many times caused by magma intrusions.
其他文献
Analysis of Error-Contaminated Survival Data
Covariate measurement error has attracted extensive interest in survival analysis.Since Prentice(1982),a large number of inference methods have been developed to handle error-contaminated data,and mos
会议
Additive hazards modelMeasurement errorSurvival analysis
Partially Linear Single-Index Regression for Accelerated Failure Time Models
In survival analysis,Accelerated Failure Time(AFT)models are very useful in modeling the relationship between failure times and associated covariates,where covariate effects are usually assumed to app
会议
Accelerated Failure Time ModelMisspecificationPartially Linear Single Index Mo
A joint selection of designs and models for optimal forecasting in possibly misspecified polynomial
The classical optimal design methods have the capability of determining designs to achieve estimation or prediction efficiency in situations where the working model is correctly specified.
会议
Information criterionmean-squared prediction errormodel selectionoptimality c
Some Statistical Problems Related to Big-Data
One key challenge with big-data is that it may not fit or cannot be processed in a single machine.A common approach to statistical learning in this setting is to randomly split the data among m machin
会议
Distributed learningM-estimationEmpirical risk minimizationBig dataHigh orde
Graphical Model Estimation in Heterogenous Populations
We introduce a general framework for estimation of inverse covariance,or precision,matrices from heterogeneous populations.
会议
Graphical ModelsHigh DimensionsHeterogenous PopulationsGraph LaplacianCluste
B-SPLINE COPULA AND ITS ESTIMATION
Bakers distribution is a method proposed to construct multivariate distributions using order statistics with given marginal distributions.
会议
Baker's distributionBernstein copulaB-spline basis functionOrder statist
Sensitive Subpopulation Finding with Biomarkers in a Randomized Clinical Trial
The benefits and challenges of incorporating biomarkers into the development of anticancer agents have been increasingly discussed.
会议
biomarkermolecular-targeted agentBayesian statisticsrandomized phase Ⅱ trial
Stationarity and quasi-stationarity for birth-death processes
After reviewing quasi-stationary distributions for birth-death processes with infinity natural and entrance boundaries,we prove that there exists a unique quasi-stationary distribution for the minimal
会议
birth-death processquasi-stationary distributioninfinity boundarynon-uniquene
Investigations on Multiple Imputation
In this presentation we investigated some properties related to multiple imputation,including: How to select variables included in the multiple imputation; Tipping point on multiple imputation using N
会议
Multiple ImputationMissing data
Smart causal machine learner that combines CT image and RNA-seq markers for cancer diagnosis and pre
The current paradigm for disease risk prediction and association analysis is to use unstructured variables for classification and testing.Less attention has been paid to structured data.
会议
Causal inferencemachine learningsufficient dimension reductionovarian cancer