分数阶长短波方程的整体光滑解

本文研究了分数阶长短波方程组的周期初边值问题,运用一致先验估计和Galerkin方法证明了分数阶长短波方程整体光滑解的存在性和唯一性.     

Empirical Likelihood Inference for the Rao‐Hartley‐Cochran Sampling Design

The Hartley‐Rao‐Cochran sampling design is an unequal probability sampling design which can be used to select samples from finite populations. We propose to adjust the empirical likelihood approach for the Hartley‐Rao‐Cochran sampling design. The approach proposed intrinsically incorporates sampling weights, auxiliary information and allows for large sampling fractions. It can be used to construct confidence intervals. In a simulation study, we show that the coverage may be better for the empirical likelihood confidence interval than for standard confidence intervals based on variance estimates. The approach proposed is simple to implement and less computer intensive than bootstrap. The confidence interval proposed does not rely on re‐sampling, linearization, variance estimation, design‐effects or joint inclusion probabilities.     

Hypothesis Testing in a Rayleigh Diffusion Model

Applying the large and moderate deviations for the log-likelihood ratio of the Rayleigh diffusion model, we give the negative regions in testing Rayleigh diffusion model and obtain the decay rates of the error probabilities.     

A class of partially linear transformation models for recurrent gap times

In this article, we propose a general class of partially linear transformation models for recurrent gap time data, which extends the linear transformation models by incorporating non linear covariate effects and includes the partially linear proportional hazards and the partially linear proportional odds models as special cases. Both global and local estimating equations are developed to estimate the parametric and non parametric covariate effects, and the asymptotic properties of the resulting estimators are established. The finite-sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a clinic study on chronic granulomatous disease is provided.     

Rank repeated measures analysis of covariance

When analyzing a response variable at the presence of both factors and covariates, with potentially correlated responses and violated assumptions of the normal residual or the linear relationship between the response and the covariates, rank-based tests can be an option for inferential procedures instead of the parametric repeated measures analysis of covariance (ANCOVA) models. This article derives a rank-based method for multi-way ANCOVA models with correlated responses. The generalized estimating equations (GEE) technique is employed to construct the proposed rank tests. Asymptotic properties of the proposed tests are derived. Simulation studies confirmed the performance of the proposed tests.     

Closed-form likelihood estimation for one type of affine point processes

ABSTRACT

This paper presents a closed-form likelihood approximation for one type of affine point processes widely used in financial credit risk models. We proceed by first conjecturing the concrete series form of the transition density, verifying our postulation and then establishing the related coefficients by means of Kolmogorov equations. The asymptotic properties of the maximum-likelihood estimators (MLEs) are given in the end.     

Comparative Study of Generalized Estimating Equations and Logistic Regressions on Different Sample Sizes and Correlation Levels

In this study, it was aimed to determine accuracy of generalized estimating equations versus logistic regressions on different correlation levels and sample sizes. For this aim, two methods were compared with different sample sizes 10, 25, 50 and 100 and correlation levels 0.0, 0.3, 0.5 and 0.8. Result of this study showed that using generalized estimating equations could be preferred versus logistic regression when the sample size is over than 25 and correlation level is higher than 0.3 on data taken from studies with repeated measurements, but logistic regression could be better when the autocorrelations do not exist.     

A comparison study on modeling of clustered and overdispersed count data for multiple comparisons

Data collected in various scientific fields are count data. One way to analyze such data is to compare the individual levels of the factor treatment using multiple comparisons. However, the measured individuals are often clustered – e.g. according to litter or rearing. This must be considered when estimating the parameters by a repeated measurement model. In addition, ignoring the overdispersion to which count data is prone leads to an increase of the type one error rate. We carry out simulation studies using several different data settings and compare different multiple contrast tests with parameter estimates from generalized estimation equations and generalized linear mixed models in order to observe coverage and rejection probabilities. We generate overdispersed, clustered count data in small samples as can be observed in many biological settings. We have found that the generalized estimation equations outperform generalized linear mixed models if the variance-sandwich estimator is correctly specified. Furthermore, generalized linear mixed models show problems with the convergence rate under certain data settings, but there are model implementations with lower implications exists. Finally, we use an example of genetic data to demonstrate the application of the multiple contrast test and the problems of ignoring strong overdispersion.     

环境规制能否有效驱动高质量发展？——基于人力资本视角的理论与经验分析

在加强生态文明建设和扩大就业的背景下,环境规制能否同时实现环境保护、绿色就业与高质量发展等多重目标已成为亟待解决的重大问题。构建一种操作便捷的高质量发展评价指标,将其分解为结构效应、技术效应及规制效应,在统一框架内剖析环境规制影响高质量发展的人力资本机制,并使用联立方程空间自回归模型和省际面板数据进行检验,探究在各类人力资本因素调节下环境规制对高质量发展的非线性效应。研究发现:（1）环境规制能通过人力资本积累、产业结构升级、节能减排技术创新等途径影响高质量发展。（2）环境规制通过与人力资本溢价的动态匹配,能进一步推动产业结构升级和节能减排技术创新,助益高质量发展。（3）环境规制在人力资本因素调节下对高质量发展存在非线性影响。总体而言,人力资本因素的改善有利于充分发挥环境规制对高质量发展的倒逼效应;提升人力资本质量是当前调控人力资本因素、释放环境规制高质量发展效应的政策重点。（4）中国高质量发展存在显著为正的空间溢出效应,地方政府在环境问题中缺乏协同治理,削弱了这种空间溢出效应,因此全局层面的高质量发展有较大提升空间。充分激发环境规制的人力资本积累效应,从单纯注重人力资本“量”的扩张转向“质”的提升,实现区域协同治理,这对有效改善环境规制的高质量发展效应至关重要。     

带有马尔可夫调制和跳的随机微分延迟方程Euler方法的强相合性

本文主要研究了下列形式的随机微分延迟方程：dX（t） =f（X（t） ,X（t -τ（t） ） ,r（t） ）dt ＋g（X（t） ,X（t -τ（t） ） ,r（t） ）dW（t） ＋h（X（t） ,X（t -τ（t） ）, r（t） ）dN（t） 0≤t≤T.考虑了时间延迟．r（t）为变量，Euler方法数值解；给出并且证明了Euler方法的强相合性定理，即Euler方法数值解均方意义下局部收敛于精确解．