Parallel tempering for dynamic generalized linear models

ABSTRACT

Markov chain Monte Carlo (MCMC) methods can be used for statistical inference. The methods are time-consuming due to time-vary. To resolve these problems, parallel tempering (PT), as a parallel MCMC method, is tried, for dynamic generalized linear models (DGLMs), as well as the several optimal properties of our proposed method. In PT, two or more samples are drawn at the same time, and samples can exchange information with each other. We also present some simulations of the DGLMs in the case and provide two applications of Poisson-type DGLMs in financial research.     

Sequential Pattern Analysis: A Statistical Investigation of Sequence Length and Support

In sequential pattern analysis, the frequency of patterns is evaluated by the support. While computed efficiently from large databases, we show that the support cannot be compared between different databases, since it is influenced by the actual sequence length distribution. Models for this sequence length distribution are surveyed. One of these models, the Good distribution, appears to be sufficiently flexible for practice. It is used to exemplify an approach for adjusting the relative support such that the resulting adjusted support values are better comparable between different databases. We illustrate our findings with texts from the bilingual FinDe corpus.     

Reliability Research of Dependent Failure Systems Using Copula

The computation of reliability characteristics of a system that consists of dependent components sometimes becomes difficult, especially when a specific type of dependence is not identified. In this paper, some systems with arbitrary dependent components are studied using copula. In the system, the components are dependent on each other and the dependent relations may be either linear or nonlinear correlation. The efficient formulas are presented to compute the reliability characteristics, such as reliability function, failure rate and meantime to failure of series, parallel and k-out-of-n systems. The reliability functions of dependant systems are compared with independent system. At last, the numerical examples are presented to illustrate the results obtained in this paper.     

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.     

Model Averaging for Prediction With Fragmentary Data

ABSTRACT

One main challenge for statistical prediction with data from multiple sources is that not all the associated covariate data are available for many sampled subjects. Consequently, we need new statistical methodology to handle this type of “fragmentary data” that has become more and more popular in recent years. In this article, we propose a novel method based on the frequentist model averaging that fits some candidate models using all available covariate data. The weights in model averaging are selected by delete-one cross-validation based on the data from complete cases. The optimality of the selected weights is rigorously proved under some conditions. The finite sample performance of the proposed method is confirmed by simulation studies. An example for personal income prediction based on real data from a leading e-community of wealth management in China is also presented for illustration.     

玻利维亚锡矿工的阶级意识——读《我们吃矿,矿吃我们》

<正>《我们吃矿,矿吃我们》②是美国女性人类学家纳什(June Nash)关于玻利维亚锡矿工人的经典民族志作品。纳什于1969年到玻利维亚锡矿山做田野,当时她42岁,还带着一个女儿,整个1970年她都在田野中。调查的敏感性使得她被矿工和CIA同时监视,但她最终获得了矿工的接纳。1971年她着手整理矿工Juan Rojas的口述历史,于1976年以西班牙文发表。《我们吃矿,矿吃我们》初版于1979年,1993年该书再版时,     

接触式低温固定中样品内部传热过程的分析

建立了用于电子显微镜生物样品制备的接触式低温固定法中的传热过程模型,并求得了一维常物性条件下的精确解。讨论了样品内部冷却速率的一些变化规律及其与样品初始温度和固化温度的关系,为实际的低温固定操作提供了理论指导。     

几种传输线的场分布

求开放平板线、外正三角形內圆同轴线、外方內圆同轴线、外正六边形內圆同轴线的特性阻抗而建立的精确保角变换的基础上,本文进一步讨论了显式逆变换函数,从而求得了这几种传输线的场分布的闭合表达式。由于所用保角变换的精确性,所得的显式场分布在内导体和外导体的内接圆尺寸之比小于0.5in。基本上是准确的,在这个尺寸比稍大些时也可作为参考。这些场分布对于了解传输线的功率容量,计算衰减常数,考虑功率耦合,设计有关的有源器件等都是必不可少的。文中获得的几种传输线的场分布的显著特点是计算方便,在一般实用范围內有足够的精度。     

A Note on Inconsistency of NPMLE of the Distribution Function from Left Truncated and Case I Interval Censored Data

We show that under reasonable conditions the nonparametric maximum likelihood estimate (NPMLE) of the distribution function from left-truncated and case 1 interval-censored data is inconsistent, in contrast to the consistency properties of the NPMLE from only left-truncated data or only interval-censored data. However, the conditional NPMLE is shown to be consistent. Numerical examples are provided to illustrate their finite sample properties.     

基于多变量混合Poisson分布的最优BMS设计

机动车辆保险精算中的奖惩系统（Ｂｏｎｕｓ－ＭａｌｕｓＳｙｓｔｅｍ,ＢＭＳ）的研究主要集中于汽车第三者责任保险的场合,ＪｅａｎＬｅｍａｉｒｅ在［１］中对此作了详细的探讨,本文作者在［２］中讨论了机动车辆车损险的分类最优ＢＭＳ,孟生旺在［３］中讨论了机动...