Objective Bayesian inference for the ratio of the scale parameters of two Weibull distributions

The Weibull distribution is widely used due to its versatility and relative simplicity. In our paper, the non informative priors for the ratio of the scale parameters of two Weibull models are provided. The asymptotic matching of coverage probabilities of Bayesian credible intervals is considered, with the corresponding frequentist coverage probabilities. We developed the various priors for the ratio of two scale parameters using the following matching criteria: quantile matching, matching of distribution function, highest posterior density matching, and inversion of test statistics. One particular prior, which meets all the matching criteria, is found. Next, we derive the reference priors for groups of ordering. We see that all the reference priors satisfy a first-order matching criterion and that the one-at-a-time reference prior is a second-order matching prior. A simulation study is performed and an example given.     

The discrepancy of P-values and posterior probability: Two-sided hypothesis of variance of normal distribution with unknown mean

This article is concerned with the comparison of P-value and Bayesian measure in point null hypothesis for the variance of Normal distribution with unknown mean. First, using fixed prior for test parameter, the posterior probability is obtained and compared with the P-value when an appropriate prior is used for the mean parameter. In the second, lower bounds of the posterior probability of H₀ under a reasonable class of prior are compared with the P-value. It has been shown that even in the presence of nuisance parameters, these two approaches can lead to different results in the statistical inference.     

Some novel results on pairwise quasi-asymptotical independence with applications to risk theory

In this article we obtain some novel results on pairwise quasi-asymptotically independent (pQAI) random variables. Concretely speaking, let X₁, …, X_n be n real-valued pQAI random variables, and W₁, …, W_n be another n non negative and arbitrarily dependent random variables, but independent of X₁, …, X_n. Under some mild conditions, we prove that W₁X₁, …, W_nX_n are still pQAI as well. Our result is in a general setting whether the primary random variables X₁, …, X_n are heavy-tailed or not. Finally, a special case of above result is applied to risk theory for investigating the finite-time ruin probability for a discrete-time risk model with a wide type of dependence structure.     

A Mann–Whitney type effect measure of interaction for factorial designs

We propose a measure for interaction for factorial designs that is formulated in terms of a probability similar to the effect size of the Mann–Whitney test. It is shown how asymptotic confidence intervals can be obtained for the effect size and how a statistical test can be constructed. We further show how the test is related to the test proposed by Bhapkar and Gore [Sankhya A, 36:261–272 (1974)]. The results of a simulation study indicate that the test has good power properties and illustrate when the asymptotic approximations are adequate. The effect size is demonstrated on an example dataset.     

Three-group ROC predictive analysis for ordinal outcomes

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning, and credit scoring. The receiver operating characteristic (ROC) surface is a useful tool to assess the ability of a diagnostic test to discriminate among three-ordered classes or groups. In this article, nonparametric predictive inference (NPI) for three-group ROC analysis for ordinal outcomes is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modeling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. This article also includes results on the volumes under the ROC surfaces and consideration of the choice of decision thresholds for the diagnosis. Two examples are provided to illustrate our method.     

The performance of model averaged tail area confidence intervals

We investigate the exact coverage and expected length properties of the model averaged tail area (MATA) confidence interval proposed by Turek and Fletcher, CSDA, 2012, in the context of two nested, normal linear regression models. The simpler model is obtained by applying a single linear constraint on the regression parameter vector of the full model. For given length of response vector and nominal coverage of the MATA confidence interval, we consider all possible models of this type and all possible true parameter values, together with a wide class of design matrices and parameters of interest. Our results show that, while not ideal, MATA confidence intervals perform surprisingly well in our regression scenario, provided that we use the minimum weight within the class of weights that we consider on the simpler model.     

基于认知理论的二语听力理解研究

二语听力理解是一个复杂的过程,受多种认知因素的影响。本研究考察了兴趣和背景知识这两个认知因素在听力理解中所起的作用以及性别对以上关系可能产生的影响。研究结果表明,兴趣和背景知识具有相关性,两者共同促进听力理解,但背景知识对听力理解的影响更大。另外,性别也影响着兴趣、背景知识和听力理解之间的关系。性别差异明显带来了兴趣和知识结构的差异,这些差异最终导致听者在听力理解上的不同表现。     

合同案件民事审判中法官自由裁量权刍议——以对事实的认定为例

合同案件民事审判中法官自由裁量权主要包括举证责任分配的自由裁量,判断证据之证据能力即合法性的自由裁量和适用证明标准的自由裁量。当前,合同案件民事审判中法官自由裁量质量不高且比较混乱,基本没有规则可循。要搞好合同案件民事审判中法官对事实认定的自由裁量,必须在思想和组织上高度重视,加强对事实认定方面在判决书中的说理和公开审判制度,加强监督和对错案的纠正。     

日内知情交易概率测度及事件影响研究

在EKOP模型测度PIN的基础上,通过建立时变交易到达率模型,滚动计算日内知情交易概率,并将PIN测度与事件研究相结合,对比了不同规模公司股票在事件日前后PIN的变化情况。实证结果表明我国股市存在信息泄露情况,尤其是小规模公司股票在公告日前一天知情交易明显增加;前一笔知情交易对当前非知情交易有削弱作用,但对当前知情交易有加强作用,可以进一步解释交易的集簇现象：日内PIN对信息的刻画更加准确,但也发现在公共事件发生后第二天PIN仍会增加,这表明市场上存在信息的学习者,需要对引起PIN增加的原因进行更准确的分析。     

工程车辆液力变矩器与发动机匹配的研究

对工程车辆中液力变矩器与发动机匹配的原则、评价指标和评价方法进行了分析研究，并结合工程车辆中使用工况比较复杂的装载机，进行了液力变矩器与发动机匹配评价的实例分析．