The non parametric regression estimate with dependent measurement errors

ABSTRACT

Non parametric regression estimation with measurement errors data has received great attention, and deconvolution local polynomial estimators can be used to deal with the problem that the errors are independent of other variables in the literature. In this article, the copula method is applied to tackle the case that the errors may depend on covariates, and the asymptotic properties of the resulting estimators are derived. Two simulations are conducted to illustrate the performance of the proposed estimators.     

Modeling of covariance structures of random effects and random errors in linear mixed models

Abstract

In this paper, we discuss how to model the mean and covariancestructures in linear mixed models (LMMs) simultaneously. We propose a data-driven method to modelcovariance structures of the random effects and random errors in the LMMs. Parameter estimation in the mean and covariances is considered by using EM algorithm, and standard errors of the parameter estimates are calculated through Louis’ (1982 Louis, T.A. (1982). Finding observed information using the EM algorithm. J. Royal Stat. Soc. B 44:98–130. [Google Scholar]) information principle. Kenward’s (1987 Kenward, M.G. (1987). A method for comparing profiles of repeated measurements. Appl. Stat. 36:296–308.[Crossref], [Web of Science ®] , [Google Scholar]) cattle data sets are analyzed for illustration,and comparison to the literature work is made through simulation studies. Our numerical analysis confirms the superiority of the proposed method to existing approaches in terms of Akaike information criterion.     

Bayesian Analysis of Two-Regime Threshold Autoregressive Moving Average Model with Exogenous Inputs

We consider Bayesian analysis of threshold autoregressive moving average model with exogenous inputs (TARMAX). In order to obtain the desired marginal posterior distributions of all parameters including the threshold value of the two-regime TARMAX model, we use two different Markov chain Monte Carlo (MCMC) methods to apply Gibbs sampler with Metropolis-Hastings algorithm. The first one is used to obtain iterative least squares estimates of the parameters. The second one includes two MCMC stages for estimate the desired marginal posterior distributions and the parameters. Simulation experiments and a real data example show support to our approaches.     

Depth Measures for Multivariate Functional Data

In this article, we address the problem of mining and analyzing multivariate functional data. That is, data where each observation is a set of possibly correlated functions. Complex data of this kind is more and more common in many research fields, particularly in the biomedical context. In this work, we propose and apply a new concept of depth measure for multivariate functional data. With this new depth measure it is possible to generalize robust statistics, such as the median, to the multivariate functional framework, which in turn allows the application of outlier detection, boxplots construction, and nonparametric tests also in this more general framework. We present an application to Electrocardiographic (ECG) signals.     

Estimating survival curves with left truncated and interval censored data via the ems algorithm

It is well-known that the nonparametric maximum likelihood estimator (NPMLE) of a survival function may severely underestimate the survival probabilities at very early times for left truncated data. This problem might be overcome by instead computing a smoothed nonparametric estimator (SNE) via the EMS algorithm. The close connection between the SNE and the maximum penalized likelihood estimator is also established. Extensive Monte Carlo simulations demonstrate the superior performance of the SNE over that of the NPMLE, in terms of either bias or variance, even for moderately large Samples. The methodology is illustrated with an application to the Massachusetts Health Care Panel Study dataset to estimate the probability of being functionally independent for non-poor male and female groups rcspectively.     

论希望的逻辑结构

某人有某种希望意指他希望某个命题为真,因而希望是关于命题的模态.希望逻辑是研究希望模态命题之间的逻辑关系.合理的希望是演绎封闭的、一致的、自我肯定的,等等,这些性质可以构成希望逻辑的公理.希望的一个重要的性质是,人们希望不一定为真,但是人们希望所希望的为真;它是希望逻辑的特有公理,可称为“希望公理”.借助于可能世界语义学通过选择不同的公理,可得到一些完全且可靠的希望逻辑系统.     

浅析当前国际环境和国际政治斗争给大学生带来的影响

本文概述了当前的国际环境和国际政治斗争的新变化 ,分析了国际环境和国际政治斗争给大学生带来的影响 ;对新形势下 ,高等学校如何抵制和防范西方敌对势力的渗透和颠覆进行了初步的探讨。     

魏尔伦诗歌中的音乐象征

魏尔伦提出音乐先于一切的诗学理论,重视音乐性在诗歌创作中的地位.他用语言模仿乐音,以独特的声响打通人的感官,实现感觉挪移,以求达成波德莱尔的横向应和.诗人借助再现的音乐表现手法,使诗意如音乐回环往复,从而推动语言的所指多层次地向纵深扩展,最终达到表层和深层的纵向应和.复调作曲技巧的运用,既构建了立体有形的外部世界,又表达了无形无边的人类情感,实现了横向应和与纵向应和的结合,诗义直达无限.魏尔伦的诗歌通过有形与无形之间无限的展示空间,较为全面地表现世界和人性的本质.由此,魏尔伦以音乐语言继承和发展了波德莱尔的应和理论,丰富了象征主义诗歌的创作手法,奠定了自己象征派代表诗人的地位.     

伍德沃德-霍夫曼规则来源之争

简要介绍了美国化学家E．J．科里(E．J．Comy，1928-)对伍德沃德-霍夫曼规则(Woodward-Hoffmann rules)来源优先权之争的来龙去脉以及R．霍夫曼(Roald Hoffmann，1937-)对昔日往事的回顾，有助于理解伍德沃德-霍夫曼规则来源之争。     

《圆圆曲》主题之争及思考

对吴伟业《圆圆曲》的主题,争议向来较多,大致有讽刺说、同情不幸说、歌颂爱情说、兴亡感慨说等诸种。通过对吴伟业生平思想、《圆圆曲》的创作背景以及作品内容真实性等各方面的探讨,认为《圆圆曲》的主题仍然是表现对吴三桂的讽刺与批判以及对其降清价值的否定,而非同情或歌颂吴三桂。