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Let p_M(t,x,y) be the minimal heat kernel of a d-dimenional compact Riemannian manifold M for any time t\in(0,1] and x,y\in M. Using the horizontal Brown bridge on M, we prove that, for any nonnegative integers n and m, there is a constant C depending on n,m and the manifold M, such that |\nabla^n_x\nabla^m_y\ln p_M(t,x,y)|\leq C[d(x,y)/t+1/\sqrt{t}\,]^{n+m}$, which generalizes the conclusion of the higher derivatives of the logarithmic heat kernel \ln p_M(t,x,y) about single variable in \ncite{1}.     

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本文是对近十年来科学前沿热点问题之一的 全基因组关联研究(genome-wide association study, GWAS)的一个综述, 侧重于介绍其中所用到的统计分析方法, 讨论当前GWAS中存在的一些问题及挑战, 并就其发展前景作一个展望.     

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Homogeneity of variance and correlation coefficients is one of assumptions in the analysis of longitudinal data.However, the assumption can be challenged. In this paper, we mainly propose and analyze nonlinear mixed effects models for longitudinal data with exponential correlation covariance structure, intend to introduce Huber's function in the log likelihood function and get robust estimation (M-estimation) by Fisher scoring method. Score test statistics for homogeneity of variance and correlation coefficient based on M-estimation are then studied. A simulation study is carried to assess the performance of test statistics and the method we proposed in the paper is illustrated by an actual data example.     

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In this paper, we propose a regime-switching Ornstein-Uhlenbeck (O-U) stochastic mortality model with jumps, in whichthe economic and environment conditions are described by a homogenous, finite-state Markov chain. Using the idea of change of measure, we derive an exponential affine form of the fourier transform of a dampened option-type longevity derivative price.     

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??In this paper, we consider a perturbed compound Poisson risk model with dependence, where the dependence structure for the claim size and the inter-claim time is modeled by a generalized Farlie-Gumbel-Morgenstern copula. The integro equations, the Laplace transforms and the defective renewal equations for the Gerber-Shiu functions are obtained. For exponential claims, some explicit expressions are obtained, and some numerical examples for the ruin probabilities are also provided.     

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In this paper, we consider the ultra-high dimensional partially linear model, where the dimensionality p of linear component is much larger than the sample size n, and p can be as large as an exponential of the sample size n. Firstly, we transform the ultra-high dimensional partially linear model into the ultra-high dimensional linear model based the profile technique used in the semiparametric regression. Secondly, in order to finish the variable screening for high-dimensional linear component, we propose a variable screening method called as the profile greedy forward regression (PGFR) by combining the greedy algorithm with the forward regression (FR) method. The proposed PGFR method not only considers the correlation between the covariates, but also identifies all relevant predictors consistently and possesses the screening consistency property under the some regularity conditions. We further propose the BIC criterion to determine whether the selected model contains the true model with probability tending to one. Finally, some simulation studies and a real application are conducted to examine the finite sample performance of the proposed PGFR procedure.     

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??Recurrent event data usually occur in long-term studies which concern
recurrence rates of the disease. In studies of medical sciences, patients who have infected
with the disease, like cancer, were conventionally regarded as impossible to be cured. However,
with the development of medical sciences, recently those patients were found to be possibly
recovered from the disease. The recurrence rate of the events, which is of primary interest,
may be affected by the cure rate that may exist. Therefore, we proposed semiparametric
statistical analysis for recurrent event data with subjects possibly being cured. In our
approach, we present a proportional rate model for recurrence rate with the cure rate adjusted
through a Logistic regression model, and develop some estimating equations for estimation of
the regression parameters, with their large sample properties, including consistency and
asymptotic normality established. Numerical studies under different settings were conducted
for assessing the proposed methodology and the results suggest that they work well for
practical situations. The approach is applied to a bladder cancer dataset which motivated our
study.     

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??In this paper, the gamma distribution has been extended by adding an extra shape parameter, we refer to the new distribution as alpha power gamma distribution. It is found that the distribution has a relatively flexible hazard rate function. The properties of the new distribution are studied, including explicit expressions for the $s^{\text{th}}$ raw moments, moment generating function and distributions of order statistics are derived. Also, the integral expressions for the entropy, mean residual life and mean waiting time are obtained. The maximum likelihood estimators of the distribution parameters under complete sample are discussed, the Fisher information matrix is derived. Then, the estimation of the parameters under the general progressive type-II censoring is studied. Finally, the real data set is used to illustrate the practicality of the proposed distribution.     

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??Auxiliary population information is often available in finite population inference problems, and the empirical likelihood (EL) approach has been demonstrated to be flexible and useful for such problems. The present paper concerns EL when interest centers on inference for the mean of the baseline distribution under two-sample density ratio models. Although dual EL is a convenient technical tool since it has the same maximum point and maximum likelihood as DRM-based EL, it can not combine such auxiliary information into the likelihood conveniently and may have loss of efficiency. By contrast, the classical EL approach of Qin and Lawless\ucite{21} does not have this problem and incorporate seamlessly auxiliary information. Based on the EL using auxiliary information and the dual EL methods, we construct both point and interval estimations and make a careful comparison. Though the point estimation efficiency gain obtained by the former is not noticeable, we find that they may have different performances in interval estimation. In terms of coverage accuracy, the two intervals are comparable for not or moderate skewed populations, and the EL interval using auxiliary information can be much superior for severely skewed populations.     

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In this paper, for a kind of risk models with heavy-tailed and delayed claims, we derive the asymptotics of the infinite-time ruin probability and the uniform asymptotics of the finite-time ruin probability. The numerical simulation results are also presented. The results of theoretical analysis and numerical simulationshow that the influence of the delay for the claim payment is nearly negligible to the ruin probability when the initial capital and running-time are all large.     

The Distribution of the Maximum Surplus before Ruin for Two Classes of Perturbed Risk Model with Stochastic Income

In this paper, we consider the two classes of perturbed risk model with stochastic income. We set up the integro-differential equations for the distribution of the maximum surplus before ruin $\mathscr{G}(u;d). The Laplace transforms of $\mathscr{G}(u;d),d\rightarrow+\infty are obtained for exponential premium income. The explicit expressions for the distribution of the maximum surplus before ruin are derived when the two classes claim amount distributions all belong to the rational family.     

The maximum surplus before ruin for two classes of perturbed risk model

In this paper, we consider the distribution of the maximum surplus before ruin in a perturbed risk model with two independent classes of risks, in which both of the two inter-claim times have phase-type distributions. We obtain the integro-differential equations for the distribution of the maximum surplus before ruin. Explicit expressions are derived if the two classes claim amount distributions both belong to the rational family.     

带干扰phaes-type风险模型中的最大盈余及相关分布

本文考虑了索赔时间间距为phase-type分布时带干扰更新风险模型中的破产前最大盈余、破产后赤字的分布,建立了相应的积分-微分方程.最后,讨论了当索赔时间间距为Erlang(2)分布且索赔量满足指数分布时的特殊情形.     

带息力更新风险模型的一个极值分布

本文讨论了带息力的更新风险模型,得到了破产前最大盈余分布的递推公式,且在此基础上还给出了它满足的积分方程.     

一类线性混合模型的谱分解估计

谱分解估计(SDE)是新近提出的关于线性混合模型参数的一种新的估计方法,此方法的一个突出特点是同时给出固定效应参数和方差分量的显式解估计．本文就含两个方差分量的线性混合模型,对谱分解估计的性质做了进一步的研究,获得了方差分量的SDE和方差分析估计相等的充分必要条件,证明了在一定的条件下方差分量的SDE为一致最小方差无偏估计．     

线性混合模型中方差分量的估计与QR分解

在线性混合模型中, 极大似然估计是一种很重要的估计方法, 但是它常常需要通过迭代求解. 应用设计阵的QR分解, 可以把设计阵变换成上三角矩阵. 这样可以降低参与迭代运算的矩阵的阶数, 还可以减少参与运算的数据量, 从而提高运算的速度. 本文讨论了QR分解在EM算法中的应用, 并用模拟的方法验证了QR分解可以极大的提高运算的速度. 本文同时讨论了QR分解在另外一种估计方法, 即ANOVA估计中的应用.     

Some Results for Classical Risk Process with Stochastic Return on Investments

In this paper, we discuss the classical risk process with stochastic return on investment. We prove some properties of the ruin probability, the supremum distribution before ruin and the surplus distribution at the time of ruin and derive the integro-differential equations satisfied by these distributions respectively.     

一般线性混合模型中的最佳线性无偏估计和谱分解估计

该文在一般线性混合模型中, 研究了固定和随机效应线性组合的估计问题.对观测向量的协方差阵可以为奇异矩阵情形下,导出了该组合的最佳线性无偏估计,并证明了它的唯一性.在一般线性混合模型的特例, 三个小域模型下, 得到了小域均值u_i 和方差分量的谱分解估计. 进而, 获得了基于谱分解估计的两步估计均方误差的二阶逼近.     

带息双二项风险模型的破产问题

本文研究了带随机利率的双二项风险模型的破产问题,得到了描述破产严重程度的破产前盈余分布,破产持续时间分布的递推公式,有限时间破产概率的递推公式及终极破产概率满足的积分方程.     

带有相依利率和保费的离散时间模型的破产问题

考虑一类具有相依结构的离散时间风险过程,其中利率和保费收入过程为两个不同的自回归移动平均模型.利用更新递归方法,得到了破产前盈余与破产后赤字的联合分布和破产持续时间分布的递归计算公式.