Permutation tests for homogeneity based on some characterizations

In this work, non parametric tests are proposed for testing the homogeneity of two or more populations. The tests are based on recently obtained characterizations. The test procedure is based on the permutation bootstrap technique. For the two-sample case the new tests are compared with permutation tests based on the empirical characteristic function and some other tests. The comparison is fulfilled via a Monte Carlo simulation.     

A predictive leverage statistic for quantile regression with measurement errors

Application of quantile regression models with measurement errors in predictors is becoming increasingly popular. High leverage points in predictors can have substantial impacts on these models. Here, we propose a predictive leverage statistic for these models, assuming that the measurement errors follow a multivariate normal distribution, and derive its exact distribution. We compare its performance versus known predictive leverage statistics using simulation and a real dataset. The proposed statistic is shown to have desirable features. It is also the first predictive leverage statistic having its distribution derived in a closed form.     

Adaptive procedure for generalized familywise error rate control

This article considers multiple hypotheses testing with the generalized familywise error rate k-FWER control, which is the probability of at least k false rejections. We first assume the p-values corresponding to the true null hypotheses are independent, and propose adaptive generalized Bonferroni procedure with k-FWER control based on the estimation of the number of true null hypotheses. Then, we assume the p-values are dependent, satisfying block dependence, and propose adaptive procedure with k-FWER control. Extensive simulations compare the performance of the adaptive procedures with different estimators.     

Exact inference for exponential distribution with multiply Type-I censored data

In this paper, we focus on exact inference for exponential distribution under multiple Type-I censoring, which is a general form of Type-I censoring and represents that the units are terminated at different times. The maximum likelihood estimate of mean parameter is calculated. Further, the distribution of maximum likelihood estimate is derived and it yields an exact lower confidence limit for the mean parameter. Based on a simulation study, we conclude that the exact limit outperforms the bootstrap limit in terms of the coverage probability and average limit. Finally, a real dataset is analyzed for illustration.     

Heuristics for prioritizing pair-wise elicitation questions with additive multi-attribute value models

Additive value models are widely used in Multiple Criteria Decision Analysis. Direct elicitation of the value model preference parameters can impose excessive cognitive burden on the decision maker. Indirect techniques that employ pair-wise questions have been proposed for lowering the elicitation effort. In all practically relevant problems, more than a single question needs to be answered for arriving at a sufficiently precise outcome. The selection and ordering of questions affects the number of answers required for ranking the decision alternatives. However, evaluating all possible questions and answers is intractable due to the search space being, in the worst case, of factorial size. This paper develops heuristics for prioritizing pair-wise elicitation questions based on (1) necessary preference relations, (2) extreme ranks attained by the alternatives, (3) pair-wise preference indices, and (4) rank acceptability indices. We also introduce three metrics for assessing quality of a question prioritization heuristic. Numerical results allow us to identify a subset of heuristics that score well on our metrics in a variety of problem settings. This conclusion was validated in a real-world experiment where 101 subjects answered pair-wise questions to rank 10 mobile phone packages evaluated in terms of four criteria.     

MULTIPLE COMPARISONS AND SELECTION1

The selection of the “best” of k populations and subsequent prediction for this population versus “the rest” is compared with the Newman-Keuls multiple comparison procedure for “separating” populations.     

Misclassification probabilities in 23 factorial experiments

Interpretational difficulties of the 2³ factorial experiments have been illustrated previously using the Monte Carlo simulation methodology. The present theoretical study derives the surprisingly large maximum frequencies of misclassification when simple effects are judged using main effects when interactions are insignificant.     

General definition and decomposition of projectors and some applications to statistical problems

A general definition of a set of projectors for decomposing a vector as the sum of vectors belonging to disjoint subspaces not necessarily spanning the whole space is given. Such projectors are defined only over the union of the disjoint subspaces. But their extension to the whole space is of some interest in statistical problems. Explicit expressions are obtained for projectors and their extensions in terms of matrices spanning the subspaces and g-inverses. Decomposition of a projector as the sum of projectors on subspaces is obtained and applied to problems arising in correlation analysis, analysis of variance and estimation of parameters in the Gauss-Markoff model.     

论国际金融学学科体系

国际金融学是从货币金融角度研究开放经济下内外均衡同时实现问题的一门独立学科。内外均衡是在经济开放条件下面临的两个主要目标 ,这两者常常存在相互冲突的现象 ,因此 ,如何确定开放经济的内外均衡目标并进而同时实现它们 ,构成了国际金融学的主要研究对象。国际金融学具有综合性、宏观性、政策导向性等特点。如何同时实现内外均衡 ?它构成国际金融学形成、发展的主线索 ,依此可以将国际金融学的学科历史划分为三个阶段。根据上述观点 ,我们对国际金融学学科体系及教材进行了相应的全面创新     

Estimating the locations and number of change points by the sample-splitting method

This paper derives a sequential testing and estimation method for the number of change points in structural-change models. In the first step, the parameters are estimated by a one-change model. The null hypothesis that there is no structural change against the alternative of one change is tested. If the null is rejected, then the whole sample is split into two subsamples by using the estimated change point in the previous step as a cutoff point. The same procedure is repeated until the null in each subsample is accepted. We argue that this method can consistently estimate the number, locations and magnitudes of changes. Situations in which the sample splitting method fails are also discussed. Received: April 22, 1997; revised version: October 15, 1999