Designing sampling plans to capture rare objects

This article focuses on two‐phase sampling designs for a population with unknown number of rare objects. The first phase is used to estimate the number of rare or potentially rare objects in a population, and the second phase to design sampling plans to capture a certain number or a certain proportion of such type of objects. A hypergeometric‐binomial model is applied to infer the number of rare or potentially rare objects and Monte Carlo simulation based approaches are developed to calculate needed sample sizes. Simulations and real data applications are discussed. The Canadian Journal of Statistics 37: 417–434; 2009 © 2009 Statistical Society of Canada     

对系统(方程组)=-x-4x~2 6xy;=-ky-xy y~2大范围全局分析

对于推广的Lotke－Votena模型许多专家、学者在X≥0，y≥0范围内对该模型进行了完整的讨论．本文对上述模型的一种特殊模型作了较全面的定性分析，得到了该系统的11种不同的拓扑结构．     

中国神话学建设的新增长点--初论应用神话学内容的设置

中国神话的演变大量存在于古典神话、活态神话及各民族神话之间。神话的演变是不断被运用的结果,它伴随着意识形态、政治文明和文化等诸多领域的诉求。神话的运用有显性与隐性之分,也有正面与负面的差别。学者既要揭示神话被滥用的现象,也要研究它如何促进当代社会的正面发展。应用神话学属于神话学的分支,它为神话学建设提供新的增长点。     

一个有价值的逻辑起点--文学文本多层次结构问题

现象学美学家茵伽登、英美新批评派的韦勒克、沃伦以及原型批评理论家弗莱,中国魏晋时期的文学理论家刘勰等,从不同的理论立足点,不约而同地聚焦于文学文本存在方式,或者从"层次"或者从"面面观"的角度相应得出文学文本是一个多层次结构、多侧面的构成.我们所珍视的不仅在于他们见解的相近,更在于他们的不同点.以此为基点,对文学批评理论的意义是第一,为文学批评从"多层次的立体结构"来全面动态地认识"文学性"开拓了思路.第二,文本多层次立体结构意味着划出了文本本体的边界,由于各个理论的相异,又表明了文学作品多层次的结构性存在是非本质的,所以艺术作品的存在本体是建构性的和开放性的.对于文学批评来说是一个有意义的前提.第三,确认多层次立体结构的文本存在方式,意味着拓宽了文学批评方法可以介入的空间,为多种方法在文学作品的各层次间进行对话和交往,形成批评话语的间性创造了条件.     

Bootstrap confidence intervals of generalized process capability index Cpyk for Lindley and power Lindley distributions

One of the indicators for evaluating the capability of a process is the process capability index. In this article, bootstrap confidence intervals of the generalized process capability index (GPCI) proposed by Maiti et al. are studied through simulation, when the underlying distributions are Lindley and Power Lindley distributions. The maximum likelihood method is used to estimate the parameters of the models. Three bootstrap confidence intervals namely, standard bootstrap (SB), percentile bootstrap (PB), and bias-corrected percentile bootstrap (BCPB) are considered for obtaining confidence intervals of GPCI. A Monte Carlo simulation has been used to investigate the estimated coverage probabilities and average width of the bootstrap confidence intervals. Simulation results show that the estimated coverage probabilities of the percentile bootstrap confidence interval and the bias-corrected percentile bootstrap confidence interval get closer to the nominal confidence level than those of the standard bootstrap confidence interval. Finally, three real datasets are analyzed for illustrative purposes.     

Further Results on the Limiting Distribution of GMM Sample Moment Conditions

In this article, we examine the limiting behavior of generalized method of moments (GMM) sample moment conditions and point out an important discontinuity that arises in their asymptotic distribution. We show that the part of the scaled sample moment conditions that gives rise to degeneracy in the asymptotic normal distribution is T-consistent and has a nonstandard limiting distribution. We derive the appropriate asymptotic (weighted chi-squared) distribution when this degeneracy occurs and show how to conduct asymptotically valid statistical inference. We also propose a new rank test that provides guidance on which (standard or nonstandard) asymptotic framework should be used for inference. The finite-sample properties of the proposed asymptotic approximation are demonstrated using simulated data from some popular asset pricing models.     

On ratio estimators in two phase sampling under size stratification and estimation over two successive occasions

Adopting size stratification when the auxiliary character is approximated by a continuous uniform distribution, a double sampling ratio strategy has been suggested. this sampling strategy has been compared with some of the known sampling strategies. the applicability of this strategy to sampling on two successive occasions has also been investigated     

Exploring the role of gain versus loss framing and point of reference in messages to reduce human–bear conflicts

As a fundamental social process, communication can help natural resource managers prevent or manage many human–wildlife conflicts, but research on how to present effectively information that contributes to the reduction of human–wildlife conflicts is scant. We examined the effectiveness of point-of-reference and gain-versus-loss framing in heightening intentions to prevent human–black bear conflicts. We randomly assigned 811 participants to one of six message conditions as part of a 3 (point of reference: family versus community versus bear) × 2 (message framing: gain versus loss) between-subjects factorial design or a control condition. The findings show that a match between loss framing and low-construal referencing point (e.g., family-referencing), and a congruency between gain framing and high-construal referencing point (e.g., bear-referencing) lead to higher risk perception and behavioral intentions. This study provides guidance for continuing research and design of risk communication in the context of human–bear conflicts.     

Maximum likelihood estimation of the parameters of a multiple step-stress model from the Birnbaum-Saunders distribution under time-constraint: A comparative study

The cumulative exposure model (CEM) is a commonly used statistical model utilized to analyze data from a step-stress accelerated life testing which is a special class of accelerated life testing (ALT). In practice, researchers conduct ALT to: (1) determine the effects of extreme levels of stress factors (e.g., temperature) on the life distribution, and (2) to gain information on the parameters of the life distribution more rapidly than under normal operating (or environmental) conditions. In literature, researchers assume that the CEM is from well-known distributions, such as the Weibull family. This study, on the other hand, considers a p-step-stress model with q stress factors from the two-parameter Birnbaum-Saunders distribution when there is a time constraint on the duration of the experiment. In this comparison paper, we consider different frameworks to numerically compute the point estimation for the unknown parameters of the CEM using the maximum likelihood theory. Each framework implements at least one optimization method; therefore, numerical examples and extensive Monte Carlo simulations are considered to compare and numerically examine the performance of the considered estimation frameworks.     

Weighted Median of the Data in Solving Least Absolute Deviations Problems

We consider the weighted median problem for a given set of data and analyze its main properties. As an illustration, an efficient method for searching for a weighted Least Absolute Deviations (LAD)-line is given, which is used as the basis for solving various linear and nonlinear LAD-problems occurring in applications. Our method is illustrated by an example of hourly natural gas consumption forecast.