Decompounding discrete distributions: A nonparametric Bayesian approach

Suppose that a compound Poisson process is observed discretely in time and assume that its jump distribution is supported on the set of natural numbers. In this paper we propose a nonparametric Bayesian approach to estimate the intensity of the underlying Poisson process and the distribution of the jumps. We provide a Markov chain Monte Carlo scheme for obtaining samples from the posterior. We apply our method on both simulated and real data examples, and compare its performance with the frequentist plug-in estimator proposed by Buchmann and Grübel. On a theoretical side, we study the posterior from the frequentist point of view and prove that as the sample size n→∞, it contracts around the “true,” data-generating parameters at rate $1/\sqrt{n}$, up to a $\log n$ factor.     

Bain: a program for Bayesian testing of order constrained hypotheses in structural equation models

This paper presents a new statistical method and accompanying software for the evaluation of order constrained hypotheses in structural equation models (SEM). The method is based on a large sample approximation of the Bayes factor using a prior with a data-based correlational structure. An efficient algorithm is written into an R package to ensure fast computation. The package, referred to as Bain, is easy to use for applied researchers. Two classical examples from the SEM literature are used to illustrate the methodology and software.     

Differential equation model of carbon dioxide emission using functional linear regression

Carbon dioxide is one of the major contributors to Global Warming. In the present study, we develop a differential equation to model the carbon dioxide emission data in the atmosphere using functional linear regression approach. In the proposed method, a differential operator is defined as data smoother and we use the penalized least square fitting criteria to smooth the data. The profile error sum of squares is optimized to estimate the differential operators using functional regression. The solution of the developed differential equation estimates and predicts the rate of change of carbon dioxide in the atmosphere at a particular time. We apply the proposed model to fit the emission of carbon dioxide data in the continental United States. Numerical simulations of a number of test cases depict a satisfactory agreement with real data.     

What determines the rejection of immigrants through an integrative model

This study tests different explanations of anti-immigrant attitudes through a model that incorporates aspects of group conflict, social identity and intergroup contact theories. Multigroup structural equation modelling was applied in three surveys, which tracked the same indicators in no similar economic and migratory contexts. In times of economic crisis, the perceived economic threat seems to lead more to discrimination and rejection of immigrants (in line with Group Conflict Theory), while sense of cultural threat is more likely to curb any desire for coexistence with them. Both threats show to be affected by the perceived size of the immigrant population, which increases the feeling of threat in those traditionally favourable to immigration. Other explanatory factors were also corroborated. Increasing contact with immigrants helps to lessen rejection, especially in the case of cultural threat. Effects due to insecurity were less marked and those relating to qualification were contrary to what was hypothesized.     

Ewma control chart under linear drift

An accurate numerical procedure is presented for computing the average run length (ARL) of an exponentially weighted moving average (EWMA) chart under a linear drift in the process mean. The performance of an EWMA chart is then evaluated under a linear drift in the mean. In processes where gradual linear drifts rather than abrupt changes in the mean model the shifts in the mean more accurately, an evaluation of the performance of an EWMA chart under a linear drift is more appropriate. Tables of optimal smoothing parameters and control chart limits are given which make the design of EWMA charts easy.     

B2C环境下物流配送服务满意度评价研究

文章运用结构方程模型,通过对ACSI顾客满意度指数模型进行改进,从多个角度构建了B2C环境下物流配送服务顾客满意度(DCS)测评模型,并设计了调查问卷进行实证研究。在收集了相关数据之后,利用SPSS及AMOS软件对所构建的结构方程模型进行了检验。研究结果表明,物流配送服务顾客满意度(DCS)测评模型对B2C环境下的物流配送服务满意度具有较好的解释力。     

添加剂滥用引发的食品安全事件与公众恐慌行为研究

随着各种食品安全事件的频发,食品安全越来越受到消费者的关注和担忧。其中,添加剂风险已成为食品安全风险中比较突出的风险之一。文章基于江苏省内经济发展程度存在显著差异的南部(苏南)、中部(苏中)、和北部(苏北)三个地区657名消费者的实际调研数据,以计划行为理论与结构方程模型为主要分析工具,研究了影响公众食品添加剂安全风险感知及其恐慌行为的主要因素,并提出了相应的政策建议。     

Parameter identification for a stochastic logistic growth model with extinction

We consider a stochastic logistic growth model given by a stochastic differential equation, for which extinction can occur. We first propose appropriate adaptation of some standard inference methods when the process is observed at discrete time. Second, we show that the individual birth and death can be identified separately to some extent.     

Stochastic heat equation and martingale differences

We prove an approximation in law of the real-valued mild solution for a class of semilinear stochastic heat equation driven by an additive fractional noise using martingale differences under suitable assumptions.     

Pooling multivariate data

In case it is doubtful whether two sets of data have the same mean vector, four estimation strategies have been developed for the target mean vector. In this situation, the estimates based on a preliminary test as well as on Stein-rule are advantageous. Two measures of relative efficiency are considered; one based on thequadratic loss function, and the other on the determinant of the mean square error matrix. A max-min rule for the size of the preliminary test of significance is presented. It is demonstrated that the shrinkage estimator dominates the classical estimator, whereas none of the shrinkage estimator and the preliminary test estimator dominate each other. The range in the parameter space where preliminary test estimator dominates shrinkage is investigated analytically and computationally. It is found that the shrinkage estimator outperform the preliminary test estimator except in a region around the null hypothesis. Moreover, for large values of a, the level of statistical significance, shrinkage estimator dominates the preliminary test estimator uniformly. The relative dominance of the estimators is presented.