江苏产研院:架两世界桥梁,迎产学研挑战

从表面上看,大学和产业似乎自然而然是结合对象:大学创造技术,产业运用技术来制造产品,两者应是终身伴侣.大学和产业之间确实有着许多成功的合作伙伴关系.然而,就像一些婚姻一样,双方平稳相处是很有挑战性的.     

A simple method for constructing confounded designs for mixed factorial experiments

This paper presents the sinplesr procedure that uses wodular aryithmetic for constructing confounded designs for mixed factorial experiments. The present procedure and the classical one for confounding in symmetrical factorial experiments are both at the same mathema.tical level. The present procedure is written for

practitioners and is lllustrared with several examples.     

Estimation in the bivariate poisson distribution and hypothesis testing concerning independence

Estimation procedures in the bivariate Poisson distribution are briefly reviewed and some errors in the literature are corrected. Asymptotic efficiencies are reexamined for both symmetric and asymmetric cases. Six hypothesis testing procedures, including three studied by Kocherlakota and Kocherlakota (1985), for independence are evaluated by using Monte Carlo simulations.     

Empirical bayes shrinkage estimation of reliability in the exponential distribution

In this paper we propose two empirical Bayes shrinkage estimators for the reliability of the exponential distribution and study their properties. Under the uniform prior distribution and the inverted gamma prior distribution these estimators are developed and compared with a preliminary test estimator and with a shrinkage testimator in terms of mean squared error. The proposed empirical Bayes shrinkage estimator under the inverted gamma prior distribution is shown to be preferable to the preliminary test estimator and the shrinkage testimator when the prior value of mean life is clsoe to the true mean life.     

Sensitivity analysis for two control groups

In many experiments where data have been collected at two points in time (pre-treatment and post-treatment), investigators wish to determine if there is a difference between two treatment groups. In recent years it has been proposed that an appropriate statistical analysis to determine if treatment differences exist is to use the post-treatment values as the primary comparison variables and the pre-treatment values as covariates. When there are several outcome variables, we propose new tests based on residuals as alternatives to existing methods and investigate how the powers of the new and existing tests are affected by various choices of covariates. The limiting distribution of the test statistic of the new test based on residuals is given. Monte Carlo simulations are employed in the power comparisons.     

A note on information loss in analyzing a mixture model of count data

In this note we consider estimation of a mixture model of count data which is composed of two discrete random variables. Conditional and unconditional estimation procedures are given for estimating the unknown parameter(s) of interest using the likelihood function. Asymptotic relative efficiencies are given to examine the amount of information loss in using the two estimation procedures. Specifically, we study the change in asymptotic relative efficiency, if any, in different parameter settings.