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高等学校学科创新引智计划(B14019)

作品数:42 被引量:211H指数:7
相关作者:叶明华汤银才汪荣明张日权徐林更多>>
相关机构:华东师范大学安徽师范大学三明学院更多>>
发文基金:高等学校学科创新引智计划国家自然科学基金国家社会科学基金更多>>
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42 条 记 录,以下是 1-10
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超高维数据边际经验似然独立筛选方法(英文)被引量:1
2019年
可加模型通过协变量函数对响应变量起作用,是更加灵活的非参统计模型.当协变量个数大于样本数且以指数阶增大时,将维数降到经典方法可解决的范围是统计学家急需解决的问题.本文研究了超高维数据可加模型的变量筛选问题,提出了边际经验似然变量筛选方法.该方法通过排列在0点的边际经验似然率选择变量.我们证明了选择变量集以概率1渐进包含真实变量集;提出了迭代边际经验似然变量筛选方法.数据模拟和实数据分析验证了所提方法的可行性.
张俊英张日权张日权陆智萍
农业气象灾害的空间集聚与政策性农业保险的风险分散——以江、浙、沪、皖71个气象站点降水量的空间分析为例(1980—2014)被引量:4
2016年
搜集1980—2014年江、浙、沪、皖71个气象站点的降水量数据,计算其全域Moran指数,并通过Kriging空间插值和降水量距平百分率法,绘制四省(市)农业旱涝灾害的空间分布图,将农业旱涝灾害的空间分布与政策性农业保险赔付率等级的空间分布进行比对,结果发现:江、浙、沪、皖降水量具有显著的空间正相关性,且表现出波动中增强的态势,受此影响,四省(市)农业旱涝灾害也表现出显著的灾害核心区和辐射区相连的区域集聚特征,而灾害的空间集聚性易导致粮食主产区的政策性农业保险面临较高的赔付风险。据此,须注重提升农业灾害的气象预警与排洪灌溉工程建设的区域协同效应,着力从传统再保险和风险互换角度做好政策性农业保险的风险分散,关注融合国家再保险、保险交易平台和保险与资本市场对接等多重渠道的农业保险巨灾风险管理体系建设。
叶明华
关键词:气象灾害政策性农业保险
Group screening for ultra-high-dimensional feature under linear model被引量:1
2020年
Ultra-high-dimensional data with grouping structures arise naturally in many contemporary statistical problems,such as gene-wide association studies and the multi-factor analysis-of-variance(ANOVA).To address this issue,we proposed a group screening method to do variables selection on groups of variables in linear models.This group screening method is based on a working independence,and sure screening property is also established for our approach.To enhance the finite sample performance,a data-driven thresholding and a two-stage iterative procedure are developed.To the best of our knowledge,screening for grouped variables rarely appeared in the literature,and this method can be regarded as an important and non-trivial extension of screening for individual variables.An extensive simulation study and a real data analysis demonstrate its finite sample performance.
Yong NiuRiquan ZhangJicai LiuHuapeng Li
Convergence rate of principal component analysis with local-linear smoother for functional data under a unified weighing scheme被引量:1
2020年
The unified weighing scheme for the local-linear smoother in analysing functional data can deal with data that are dense,sparse or of neither type.In this paper,we focus on the convergence rate of functional principal component analysis using this method.Almost sure asymptotic consistency and rates of convergence for the estimators of eigenvalues and eigenfunctions have been established.We also provide the convergence rate of the variance estimation of the measurement error.Based on the results,the number of observations within each curve can be of any rate relative to the sample size,which is consistent with the earlier conclusions about the asymptotic properties of the mean and covariance estimators.
Xingyu YanXiaolong PuYingchun ZhouXiaolei Xun
定数截尾数据缺失场合Frechet分布参数的近似极大似然估计被引量:3
2017年
Frechet分布是一种重要的寿命分布,本文给出了在定数截尾数据缺失场合两参数Frechet分布参数的近似极大似然估计,并通过Monto-Carlo模拟说明了本文方法的可行性.
曾林蕊汤银才窦雯
关键词:近似极大似然估计
A class of admissible estimators of multiple regression coefficient with an unknown variance
2020年
Suppose that we observe y|θ,τ∼N_(p)(Xθ,τ^(−1)I_(p)),where θ is an unknown vector with unknown precisionτ.Estimating the regression coefficient θ with known τ has been well studied.However,statistical properties such as admissibility in estimating θ with unknownτare not well studied.Han[(2009).Topics in shrinkage estimation and in causal inference(PhD thesis).Warton School,University of Pennsylvania]appears to be the first to consider the problem,developing sufficient conditions for the admissibility of estimating means of multivariate normal distributions with unknown variance.We generalise the sufficient conditions for admissibility and apply these results to the normal linear regression model.2-level and 3-level hierarchical models with unknown precisionτare investigated when a standard class of hierarchical priors leads to admissible estimators of θ under the normalised squared error loss.One reason to consider this problem is the importance of admissibility in the hierarchical prior selection,and we expect that our study could be helpful in providing some reference for choosing hierarchical priors.
Chengyuan SongDongchu Sun
Quantile treatment effect estimation with dimension reduction
2020年
Quantile treatment effects can be important causal estimands in evaluation of biomedical treatments or interventions for health outcomes such as medical cost and utilisation.We consider their estimation in observational studies with many possible covariates under the assumption that treatment and potential outcomes are independent conditional on all covariates.To obtain valid and efficient treatment effect estimators,we replace the set of all covariates by lower dimensional sets for estimation of the quantiles of potential outcomes.These lower dimensional sets are obtained using sufficient dimension reduction tools and are outcome specific.We justify our choice from efficiency point of view.We prove the asymptotic normality of our estimators and our theory is complemented by some simulation results and an application to data from the University of Wisconsin Health Accountable Care Organization.
Ying ZhangLei WangMenggang YuJun Shao
关键词:CAUSALITY
基于线性退化轨道的区间型建模分析及应用被引量:2
2018年
目前在退化试验中,产品失效一般定义为其性能退化至低于或高于一个指定临界值(单点型退化),尽管这种定义简单实用,但却不尽合理,不能完全描述产品退化失效问题.本文改进单点型退化模型,提出区间型退化模型,并讨论了退化轨道是线性时的区间退化模型问题,获得了各种线性区间退化寿命分布.本文利用数值积分和蒙特卡罗法模拟分析对比区间退化模型和单点退化模型的寿命分布,揭示区间退化和单点退化的关系.最后通过实例分析体现区间退化在实际中更为合理有效.
管强汤银才
基于Copula相依函数的安徽省气温与降雨量相关性研究被引量:6
2017年
当前全球气候变暖大背景下,气温和降雨量的交互作用引致农业气象灾害频发,给农业生产造成破坏性风险损失,因此探讨气温与降雨量之间的动态相依关系尤为重要。搜集安徽省24个气象观测站1980~2014年的气温与降雨量日数据,对原始数据进行矩平均处理,使两组数据列满足独立同分布的要求。采用非参数核估计的方法确定气温与降雨量的边缘分布。根据降雨量和气温的均匀分布散点图和频数分布直方图可知,安徽省气温和降雨量之间呈现一定程度的负相依关系,即图形中表现出气温与降雨量的上下尾之间的对称性。综上分析,选择可以刻画两个变量具有上下尾对称关系的Copula函数对气温与降雨量的相依关系进行拟合,最终在平方欧式距离最小的原则下选定二元t-Copula函数做出气温与降雨量之间的联合概率密度函数图。研究结果发现:1据安徽省气温与降雨量联合概率分布可知,当降雨量上升时,气温下降;或气温上升时,降雨量会下降,气温与降雨量之间呈现为中等负相关关系(–0.280)。2极值相关性方面,从t-Copula密度函数图和上下尾相关系数看,安徽省气温与降雨量在极值方面具有较为明显的相依关系,表现为当气温和降雨量超过正常范畴时,二者相依关系从负相关转变为正相关,此现象多出现在极端气候条件下,例如极端高温和大暴雨时气温与降雨量的正相依性。
叶明华汪荣明丁越束炯
关键词:气温降雨量COPULA函数
Empirical likelihood estimation in multivariate mixture models with repeated measurements
2020年
Multivariate mixtures are encountered in situations where the data are repeated or clustered measurements in the presence of heterogeneity among the observations with unknown proportions.In such situations,the main interest may be not only in estimating the component parameters,but also in obtaining reliable estimates of the mixing proportions.In this paper,we propose an empirical likelihood approach combined with a novel dimension reduction procedure for estimating parameters of a two-component multivariate mixture model.The performance of the new method is compared to fully parametric as well as almost nonparametric methods used in the literature.
Yuejiao FuYukun LiuHsiao-Hsuan WangXiaogang Wang
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