Pareto improvements by Pareto strategic voting under majority voting with risk loving and risk avoiding voters — A note

Voters satisfy maximin or maximax in their choices between sets of alternatives and secure a Pareto improvement by all voting strategically under simple majority voting for particular sincere preferences. Thus the assumption that strategic voting is a bad thing is challenged and the idea that we should reject voting because of the possibility of misrepresentation dismissed.     

海洋环境下萨哈林岛卡萨弗斯大桥的受力性能评估

以俄罗斯萨哈林岛卡萨弗斯跨海大桥为研究对象,由于海洋环境的影响钢梁受到严重腐蚀,损伤程度较大,有必要进行相应的受力性能评估。利用有限元模型对损伤部位进行模拟,根据锈蚀损伤程度对钢混桥极限承载能力进行了分析和评估,结果表明,桥梁破损严重但承载能力符合规范标准,并提出了改造建议和未来的研究方向。其结果具有一定的理论意义和工程实践应用价值。     

Estimation of distribution functions in measurement error models

Many practical problems are related to the pointwise estimation of distribution functions when data contain measurement errors. Motivation for these problems comes from diverse fields such as astronomy, reliability, quality control, public health and survey data.     

A generalized bivariate Bernoulli model with covariate dependence

Dependence in outcome variables may pose formidable difficulty in analyzing data in longitudinal studies. In the past, most of the studies made attempts to address this problem using the marginal models. However, using the marginal models alone, it is difficult to specify the measures of dependence in outcomes due to association between outcomes as well as between outcomes and explanatory variables. In this paper, a generalized approach is demonstrated using both the conditional and marginal models. This model uses link functions to test for dependence in outcome variables. The estimation and test procedures are illustrated with an application to the mobility index data from the Health and Retirement Survey and also simulations are performed for correlated binary data generated from the bivariate Bernoulli distributions. The results indicate the usefulness of the proposed method.     

Effect of individual observations on the Box–Cox transformation

In this paper, we consider the influence of individual observations on inferences about the Box–Cox power transformation parameter from a Bayesian point of view. We compare Bayesian diagnostic measures with the ‘forward’ method of analysis due to Riani and Atkinson. In particular, we look at the effect of omitting observations on the inference by comparing particular choices of transformation using the conditional predictive ordinate and the k _d measure of Pettit and Young. We illustrate the methods using a designed experiment. We show that a group of masked outliers can be detected using these single deletion diagnostics. Also, we show that Bayesian diagnostic measures are simpler to use to investigate the effect of observations on transformations than the forward search method.     

Confidence intervals for the comparison of two poisson distributions

Confidence interval construction the difference in mean event rates for two Index independent , Poisson samples is discussed. Intervals are derived by considering Bayes estimates of the mean event rates using a family of noninformative priors. The coverage probabilities of the proposed are compared to those of the standard Wald interval for of observed events. A compromise method of constructing interval based on the data is suggested and its properties are evaluated. The method is illustrated in several examples.     

D-optimal weighing designs and optimal chemical balance weighing designs for estimating the total weight

This paper provides D-optimal spring balance designs for estimating individual weights when the number of objects to be weighed in each weighing, B, is fixed. D-optimal chemical balance designs for estimating total weight under both homogeneous and nonhomogeneous error variances are found when the number of objects weighed in each weighing is ≥ B, a fixed number.

We indicate the restriction used in Chacko & Dey(1978) and Kageyama(1988), i.e. that chemical designs X be restricted to designs in which exactly “a” objects are replaced on the left pan and exactly “b” on the right pan in each of the weighings for a, b > 0, is unnecessary.     

A plant-capture approach for achieving complete coverage of a population

Sightings of, any member of a target population of unknown size occur according to a homogeneous Poisson process. The Poisson processes are independent and have a common rate. Individuals are tagged when first sighted. The population is augmented by the insertion of known number of planted individuals who have already been tagged and whose behaviour is identical to that of the other members. Consideration is given to two stopping rules for determining, within a specified error probability, when all members of the target population have been seen. A comparison is made of the average time to termination under these two rules. It is shown that, when the target population is small, the use of plants can provide a useful reduction in the average time taken to achieve complete coverage within the specified error probability.