Estimation and testing procedures for the reliability functions of a general class of distributions

We consider here the general class of distributions proposed by Sankaran and Gupta (2005) by zeroing in on two measures of reliability, R(t) = P(X > t) and P = P(X > Y). Thereafter, we develop point estimation for R(t) and ‘P’ and develop uniformly minimum variance unbiased estimators (UMVUES). Then we derive testing procedures for the hypotheses related to different parametric functions. Finally, we compare the results using the Monte Carlo simulation method. Using real data set, we illustrate the procedure clearly.     

Rényi statistics for testing composite hypotheses in general exponential models

We introduce a family of Rényi statistics of orders r?∈?R for testing composite hypotheses in general exponential models, as alternatives to the previously considered generalized likelihood ratio (GLR) statistic and generalized Wald statistic. If appropriately normalized exponential models converge in a specific sense when the sample size (observation window) tends to infinity, and if the hypothesis is regular, then these statistics are shown to be χ²-distributed under the hypothesis. The corresponding Rényi tests are shown to be consistent. The exact sizes and powers of asymptotically α-size Rényi, GLR and generalized Wald tests are evaluated for a concrete hypothesis about a bivariate Lévy process and moderate observation windows. In this concrete situation the exact sizes of the Rényi test of the order r?=?2 practically coincide with those of the GLR and generalized Wald tests but the exact powers of the Rényi test are on average somewhat better.     

Robust Testing Procedures in Heteroscedastic Linear Models

There exist many studies which treat the robust tests in homoscedastic linear models. However, the robust testing procedure in heteroscedastic linear models has not been examined. In this article, three classes of testing procedures for testing subhypothesis in heteroscedastic linear models are developed. These are Wald-type, score-type, and drop-in dispersion tests. The asymptotic distributions of these tests are obtained under the null hypothesis and contiguous alternatives. For a robustness criterion, the maximum asymptotic bias of the level of the test for distributions in a shrinking contamination neighborhood is used and the most-efficient robust test is derived. Finally, the performance of these tests in small sample is studied by Monte Carlo simulation.     

Simple Tests for Exogeneity of a Binary Explanatory Variable in Count Data Regression Models

This article investigates power and size of some tests for exogeneity of a binary explanatory variable in count models by conducting extensive Monte Carlo simulations. The tests under consideration are Hausman contrast tests as well as univariate Wald tests, including a new test of notably easy implementation. Performance of the tests is explored under misspecification of the underlying model and under different conditions regarding the instruments. The results indicate that often the tests that are simpler to estimate outperform tests that are more demanding. This is especially the case for the new test.     

On Multi-Sided Permutation Tests

In fields such as clinical trials, the environment, epidemiology, genetics, pharmacology, social experiments, etc., situations in which the effect of a treatment can be positive on some individuals and negative on the rest may sometimes occur. In a two-sample design, this situation can be expressed by a response model where a random effect Δ in the alternative is such that , and . Such a situation is essentially different from the traditional two-sided test, in which the alternative is assumed to be active only on one of two directions. We consider alternatives in which two sub-alternatives (Δ < 0) and (Δ > 0) can be jointly active. In order to deal with such an atypical situation, we suggest to firstly apply two goodness-of-fit tests, one for the positive deviations from the empirical distribution function of control sample and the other for the negative, and then proceed with their nonparametric combination within a permutation framework. A simulation study inspects on properties of such a solution.     

A hypothesis testing procedure for the evaluation on the lifetime performance index of products with Burr XII distribution under progressive type I interval censoring

ABSTRACT

It is a very important topic these days to assessing the lifetime performance of products in manufacturing or service industries. Lifetime performance indices C_L is used to measure the larger-the-better type quality characteristics to evaluate the process performance for the improvement of quality and productivity. The lifetimes of products are assumed to have Burr XII distribution. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also developed. We use this estimator to build the new hypothesis testing algorithmic procedure with respect to a lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.     

培养研究生英语语言应用能力的教学体系研究

本文拟根据语言学、认知心理学理论 ,研究如何对研究生英语课程的教学体系 (包括教学内容、教学模式、教材建设、教学手段和方法、测试和语言评估体系及学生自主学习的方略等 )进行系统的研究和改革 ,充分运用和调动教与学的过程中各个环节的有利因素 ,致力培养和提高研究生的英语语言实际应用能力和利用英语为其专业发展服务的能力     

Central Ethical Dilemmas in Research Involving Children

We are obligated to protect individual child subjects of research, yet it is also necessary to investigate the safety and efficacy of medical treatments that benefit children as a class. The federal regulations on research with children have provided ethical guidance since 1983, but divergent interpretations persist. Since varying interpretations can lead to confusion and abuses, efforts are underway to clarify the criteria. Clarity is needed to protect individual child subjects from harm while enabling ethical research to proceed. The "pediatric rule" and the "pediatric exclusivity" incentive are important policy initiatives for promoting sound research on the medical treatment of children.     

The robustness of point optimal testing for rosenberg random regression coefficients

The literature on testing for the presence of Rosenberg's (1973) return to normalcy random coefficient model is well developed with both Shively (1988) and Brooks (1993) advocating the use of point optimal tests. This paper explores the robustness of point optimal testing for the Rosenberg alternative to two departures: the special case HildrethHouck (1968) alternative and non-normality in regression disturbances, finding the point optimal testing approach to be fairly robust to both departures.