Economic design of T<Superscript>2</Superscript> control charts with the VSSI sampling scheme

T ² charts are used to monitor a process when more than one quality variable associated with process is being observed. Recent studies have shown that the T ² chart with variable sampling size and sampling interval (VSSI) detects a small shift in the process mean vector faster than the traditional T ² chart. The paper considers an economic design of the VSSI T ² chart, in which the expected hourly loss is constructed and regarded as an objective function for optimally determining the design parameters (i.e. the maximum/minimum sample size, the longest/shortest sampling interval, and the warning/action limits) in sampling-and-charting. Furthermore, the effects of process parameters and cost parameters upon the expected hourly loss and design parameters are examined.     

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks

Likelihoods and posteriors of instrumental variable (IV) regression models with strong endogeneity and/or weak instruments may exhibit rather non-elliptical contours in the parameter space. This may seriously affect inference based on Bayesian credible sets. When approximating posterior probabilities and marginal densities using Monte Carlo integration methods like importance sampling or Markov chain Monte Carlo procedures the speed of the algorithm and the quality of the results greatly depend on the choice of the importance or candidate density. Such a density has to be ‘close’ to the target density in order to yield accurate results with numerically efficient sampling. For this purpose we introduce neural networks which seem to be natural importance or candidate densities, as they have a universal approximation property and are easy to sample from. A key step in the proposed class of methods is the construction of a neural network that approximates the target density. The methods are tested on a set of illustrative IV regression models. The results indicate the possible usefulness of the neural network approach.     

The small sample bias of Durbin's tests for serial correlation: When one of the regressors is the lagged dependent variable and the null hypothesis is true

Durbin (1970) has recently proposed two asymptotically equivalent statistics which can be used to test for the presence of serial correlation when some of the regressors are lagged dependent variables. This study reports on simulation experiments designed to compare the two statistics, in use with small samples, in terms of their tendencies to detect serial correlation when none exists. Of the two test statistics, it is found that the one based on estimated residuals detects the absence of serial correlation in the expected proportion of trials; the other statistic (Durbin's h), which involves the application of a correction factor to the Durbin-Watson statistic, gives evidence of serious small sample bias which varies with both the sample size and the assumed size of the coefficient attaching to the lagged dependent variable.     

谈高职院校科技社团在校园文化建设中的影响力——以无锡科技职业学院为例

近年来,随着国家大力支持培养技能型人才,鼓励科技创新、科学实践,高职院校学生科技社团的建设和发展日益受到重视。科技社团给学生提供了更好的学习、实践平台,在强化专业技能,提高动手能力,全面提升学生素质方面具有不可替代的作用。本文以无锡科技职业学院为例阐述了科技社团的活动形式和创新成果,强调了科技社团在高职院校文化建设中的影响。