WTO规则与我国市场经济法律体系之完善

我国入世在即,但我国现行市场经济法律制度在很多方面却与WTO的规则有相当差距.因此,完善我国市场经济法律体系刻不容缓.     

破产犯罪研究

随着市场经济的发展,破产已经成为社会经济生活中的自然现象,与之相关的破产犯罪日渐猖獗,对社会的危害也愈加严重。我国关于破产犯罪的立法存在严重缺陷和不足,不能适应打击和预防破产犯罪的需要,应加以完善。     

试论离婚之精神损害赔偿制度

离婚之精神损害有离因精神损害和离婚精神损害两种.前者是夫妻一方对另一方构成侵权行为而导致离婚,从而给一方造成精神痛苦,受害方可请求精神损害赔偿.我国新的<婚姻法>确立了这一精神损害赔偿制度,填补了我国婚姻制度的一个空缺.而后者是夫妻一方对另一方并无侵权行为,离婚本身即为构成精神损害之直接原因,如由于第三者插足、婚外恋、夫妻一方被判处徒刑等.这种离婚同样使一方受到精神损害,自然也应得精神损害赔偿.遗憾的是,新的<婚姻法>并未作此规定.因此,要完善我国离婚之精神损害赔偿制度,不仅要使离婚之精神损失赔偿的权利义务主体进一步扩大,把第三者也作为离婚之精神损害赔偿的义务主体,而且还要将离因精神损害赔偿扩大到离婚精神损害赔偿,将因婚外恋、第三者插足、因配偶一方犯罪而被判入狱和其他原因导致离婚的情况作出规定,使精神受害者得到应有的经济救济和补偿.     

Variance estimation for the 2006 French housing survey

In the 2006 French housing survey, information is collected on many aspects of housing to describe the housing stock in France and the housing conditions of French households. The basic national sample results from a multistage sampling design. Complementary samples were selected to perform accurate estimations for socio-demographic domains. Some French regions proceeded to a regional and local extension of the national sample. The variance is estimated for a region with a regional and local extension of the basic national sample.     

Synthetic double sampling s chart

This study proposes a synthetic double sampling s chart that integrates the double sampling (DS) s chart and the conforming run length chart. An optimization procedure is proposed to compute the optimal parameters of the synthetic DS s chart. The performance of the synthetic DS s chart is compared with other existing control charts for monitoring process standard deviation. The results show that the synthetic DS s chart is more effective for detecting increases in the process standard deviation for a wide range of shifts. An example is provided to illustrate the operation procedure of the synthetic DS s chart.     

Estimation of finite population mean in simple and stratified random sampling using two auxiliary variables

We propose an improved difference-cum-exponential ratio type estimator for estimating the finite population mean in simple and stratified random sampling using two auxiliary variables. We obtain properties of the estimators up to first order of approximation. The proposed class of estimators is found to be more efficient than the usual sample mean estimator, ratio estimator, exponential ratio type estimator, usual two difference type estimators, Rao (1991) estimator, Gupta and Shabbir (2008) estimator, and Grover and Kaur (2011) estimator. We use six real data sets in simple random sampling and two in stratified sampling for numerical comparisons.     

Use of online crowdsourcing platforms for gambling research

Crowdsourcing platforms like Amazon’s Mechnical Turk and Crowdflower have been touted to be a cost-effective way to collect large amounts of behavioural data. Across four large-n studies, gambling-related behaviours, tendencies and traits among participants in these labour markets were examined. In Studies 1 and 2, both conducted on Crowdflower, problem gamblers (as measured by the benchmark Problem Gambling Severity Index) comprised 24.5% and 21.9% of participants, respectively. In Study 3, conducted on Mechanical Turk, problem gamblers comprised 9.0% of participants. In Study 4, a two-wave longitudinal study conducted on Crowdflower, problem gamblers comprised 13.5% of participants in wave one and 14.8% of participants in wave two. In Studies 2 and 3, strong convergent associations were demonstrated across various measures of problem gambling tendencies and general gambling involvement. Furthermore, it was demonstrated that gambling was associated with personality traits (impulsivity, sensation-seeking, self-control), risk attitudes, affect, and behavioural risk-taking consistent with previous research. In Study 4, it was demonstrated that measures of problem gambling have acceptable test-retest reliability. Online crowdsourcing platforms appear to offer access to samples with remarkably high proportions of problem gamblers. However, this characteristic means that such samples are not necessarily representative of gambling tendencies among more general populations.     

Adaptive multiple importance sampling for Gaussian processes

In applications of Gaussian processes (GPs) where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. This is normally done by means of standard Markov chain Monte Carlo (MCMC) algorithms, which require repeated expensive calculations involving the marginal likelihood. Motivated by the desire to avoid the inefficiencies of MCMC algorithms rejecting a considerable amount of expensive proposals, this paper develops an alternative inference framework based on adaptive multiple importance sampling (AMIS). In particular, this paper studies the application of AMIS for GPs in the case of a Gaussian likelihood, and proposes a novel pseudo-marginal-based AMIS algorithm for non-Gaussian likelihoods, where the marginal likelihood is unbiasedly estimated. The results suggest that the proposed framework outperforms MCMC-based inference of covariance parameters in a wide range of scenarios.     

Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data

In this article, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences that involve estimation of parameters and their standard deviations and residuals analysis for testing the selected model are discussed. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of dichotomous variables. The proposed procedure is illustrated by a simulation data obtained from R program. Analyses are done by using R2WinBUGS package in R-program.