CONDITIONAL INFERENCE ABOUT AN EQUICORRELATION COEFFICIENT

SenGupta (1987) proposed a locally most powerful test which is globally (one sided) unbiased, and an estimator of p, the equicorrelation coefficient of a standard symmetric multivariate normal (SSMN) distribution. Here we use the idea in Williams (1984) to illustrate the construction and use of ancillary statistics to make inference about p. The test and confidence intervals based on this construction are conditionally optimal.     

Medicaid Home and Community-Based Services: How Consumer Access Is Restricted by State Policies

State Medicaid programs have expanded home and community-based services (HCBS). This article compares trends and variations in state policies for Medicaid HCBS programs in 2005 and 2010. State limitations on financial eligibility criteria and service benefits have remained stable. Although the use of consumer direction, independent providers, and family care providers has increased, some states do not have these options. The increased adoption of state cost control policies have led to large increases in persons on waiver wait lists. Access could be improved by standardizing and liberalizing state HCBS policies, but state fiscal concerns are barriers to rebalancing between HCBS and institutional services.     

红桥修禊与清代士人之心态流变

修禊作为一种古老的祭祀风俗,在历史的流变中逐渐转化为一种文人雅集的重要形式。从闻名古今的兰亭修禊开始,修禊不断地被后世文人所模仿,留下了众多的千古佳话。文章以清朝王士禛、孔尚任、卢见曾所举行的几次著名的红桥修禊为例,通过这几次文人禊集中流传下来的诗文词赋,揭示出清代文人的精神风貌和生活情趣,及在不同时期士人心态的流变。     

农民专业合作社关系变异及性质解析

我国农村普遍存在因异质成员侵入的变异农民专业合作社。经典农民专业合作社属农业产业横向一体化组织,变异农民专业合作社属农业产业纵向一体化组织,它们在组织属性、功能性质、控制结构、分配机制、利益关系等方面有着本质区别。变异农民专业合作社无法替代经典农民专业合作社的功能和作用。尽管变异农民专业合作社对我国农业产业化起到了重要作用,但是基于我国农村人多地少的特殊国情,要实现农民、农业、农村均衡发展,需要加强经典农民专业合作社的建设,通过家庭农户的合作互助促进家庭农场发展,实现我国农业适度规模、专业化生产和集约化经营,最终实现农村自我工业化和城镇化发展。     

甘肃省入境客流时空演变特征分析

经过将近30多年的发展,甘肃省入境旅游旅游业取得了长足的发展,入境旅游业的发展拓宽了甘肃省旅游产业的发展空间。但由于受到各种因素的制约,甘肃省入境客流的变化发展有着自身独特的规律和特点,特别是从甘肃省入境旅游发展的外部环境看,其时间和空间演变的特征十分典型,特别是时空分布的不平衡性是其长期以来最显著的特征。     

An online copy number variant detection method for short sequencing reads

The availability of the next generation sequencing (NGS) technology in today's biomedical research has provided new opportunities in scientific discovery of genetic information. The high-throughput NGS technology, especially DNA-seq, is particularly useful in profiling a genome for the analysis of DNA copy number variants (CNVs). The read count (RC) data resulting from NGS technology are massive and information rich. How to exploit the RC data for accurate CNV detection has become a computational and statistical challenge. We provide a statistical online change point method to help detect CNVs in the sequencing RC data in this paper. This method uses the idea of online searching for change point (or breakpoint) with a Markov chain assumption on the breakpoints loci and an iterative computing process via a Bayesian framework. We illustrate that an online change-point detection method is particularly suitable for identifying CNVs in the RC data. The algorithm is applied to the publicly available NCI-H2347 lung cancer cell line sequencing reads data for locating the breakpoints. Extensive simulation studies have been carried out and results show the good behavior of the proposed algorithm. The algorithm is implemented in R and the codes are available upon request.     

A Bayesian estimate of the concordance correlation coefficient with skewed data

Concordance correlation coefficient (CCC) is one of the most popular scaled indices used to evaluate agreement. Most commonly, it is used under the assumption that data is normally distributed. This assumption, however, does not apply to skewed data sets. While methods for the estimation of the CCC of skewed data sets have been introduced and studied, the Bayesian approach and its comparison with the previous methods has been lacking. In this study, we propose a Bayesian method for the estimation of the CCC of skewed data sets and compare it with the best method previously investigated. The proposed method has certain advantages. It tends to outperform the best method studied before when the variation of the data is mainly from the random subject effect instead of error. Furthermore, it allows for greater flexibility in application by enabling incorporation of missing data, confounding covariates, and replications, which was not considered previously. The superiority of this new approach is demonstrated using simulation as well as real‐life biomarker data sets used in an electroencephalography clinical study. The implementation of the Bayesian method is accessible through the Comprehensive R Archive Network. Copyright © 2015 John Wiley & Sons, Ltd.     

Social integration and dialect divergence in coastal Palestine

The history of Palestine has caused communities to be displaced and relocated, entailing that speech communities have been dismantled and created anew. The coastal cities of Jaffa and Gaza exemplify this reality. This study analyzes speakers from Jaffa, some of whom remained there and others residing in Gaza as refugees. Through an examination of three variables, (?), (AH), and (Q), we shed light on the effects of dialect contact while highlighting the link between dialect contact and identity formation and maintenance. All three variables are found to be in varied states of change as a result of contact with other varieties of Arabic, as well as with Modern Hebrew. We conclude that (Q), through its high social salience, works to create and maintain a sense of community identity for Jaffan refugees in Gaza at a time when the speech of the larger Jaffa community is undergoing substantial linguistic change.     

A Bivariate Distribution Family with Specified Correlation Coefficient and Given Marginals

For given continuous distribution functions F(x) and G(y) and a Pearson correlation coefficient ρ, an algorithm is provided to construct a sequence of continuous bivariate distributions with marginals equal to F(x) and G(y) and the corresponding correlation coefficient converges to ρ. The algorithm can be easily implemented using S-Plus or R. Applications are given to generate bivariate random variables with marginals including Gamma, Beta, Weibull, and uniform distributions.     

一致性分数阶优化灰色模型及其应用

传统的分数阶灰色预测模型在时间序列预测中具有较好的适应性和预测的有效性,但其累加和差分计算式比较复杂。一致性分数阶累加相对于一般的分数阶累加,形式更简单,更便于计算和理论推导。为了提高模型的适应性和预测能力,文章在CFGM(1,1)白化方程中引入一个新的可变系数,扩大了原有白化方程的适用范围,并在此基础上构建了一致性分数阶优化灰色模型,即CFOGM(1,1)模型。最优一致性分数阶阶数和可变系数通过PSO算法最小化平均相对误差获得。将构建的模型运用到两个实例中并与其他经典的灰色预测模型进行对比,结果表明所提出的模型具有较高的拟合和预测精度。