为中国人民服务

我来自加拿大安大略省的多伦多市,相信大家对这个地方并不陌生,它是大山的家乡,白求恩医生也在此出生并接受医疗培训。我所在的约克大学就有一个本科生学院是以白求恩医生的名字命名的。白求恩医生的事迹感召着我们．我们每一位获奖外国专家都将永远为我们有机会“为人民服务”,为中国人民服务而心存感激,这是我们无上的荣耀。     

USING DUMMY VARIABLES TO CHECK FOR ROUNDING ERROR IN COMPUTERIZED REGRESSION PROGRAMS*

After a brief review of the role of dummy variables in regression analysis and the current state-of-the art in rounding/truncation error detection in computerized least squares programs, this paper presents a theorem that can be used to detect this type of error whenever an analyst is running a regression program that has one (or more) dummy variables as independent variables.     

REGRESSION METHODOLOGY WITH GROSS OBSERVATION ERRORS IN THE EXPLANATORY VARIABLES***

The robustness of linear programming regression estimators is examined where the disturbance terms are normally distributed and there are observation errors in the explanatory variables. These errors are occasional gross biases between one set of observations and another. The simulation of short series data offers preliminary evidence that when these biases have a non-zero mean, MSAE estimation is more robust than least squares.     

THE EFFECTS OF INTERDISCIPLINARY EDUCATIONAL FORMATS ON CONCEPT RETENTION AND PROBLEM–SOLVING ABILITY*

The purpose of this study was to examine the effects of different interdisciplinary problem-oriented formats on a student's knowledge of and retention of disciplinary concepts and principles, his application of these concepts and principles to disciplinary problems, and his use of a discipline in his analysis of a complex problem. Performances of students enrolled in the experimental sections were compared to those of students enrolled in standard lecture-discussion sections. Regression analysis was used to analyze students' performance in order to control the effects of differences in student backgrounds. It was found that altering the pedagogical format and reward system within the experimental sections had no significant effect upon student performances in the experimental, problem-oriented program. In general, this study indicates that students taught in the standard lecture-discussion format in which grades are determined by examination over course material retain concepts and principles, apply these concepts and principles to disciplinary problems, and integrate disciplinary concepts into their analysis of complex problems as well as, if not better than, students taught in an interdisciplinary, problem-solving format.     

MATERIAL REQUIREMENTS PLANNING UNDER UNCERTAINTY

This paper presents a framework for characterizing and studying the uncertainty which can affect inventory investment and service level performance in a material requirements planning (MRP) system. It also presents the results of a simulation experiment which compared two techniques (safety stock and safety lead time) for building inventory to protect against uncertainty. The simulation results disclose consistent differences between the techniques in protecting a representative part against timing and quantity uncertainty in both demand and supply for the part. The paper not only provides some initial insights into the behavior of MRP systems under uncertainty, but also establishes some guidelines for choosing between safety stock and safety lead time.     

The Development of Peer Interaction in Infancy: Exploring the Dyadic Processes

Peer interaction is an important component of children's social repertoires that is associated with a variety of developmental outcomes and life skills. The present study provides an in‐depth study of early dyadic peer behaviors during the infancy period, during which social competence with peers is first being developed. Results from variable‐centered analyses highlight the effectiveness of behaviors, such as offering objects to peers, and point to the importance of the social context set by a peer's prior social behavior and processes for eliciting peer responses. Findings from person‐centered analyses reveal marked individual differences in the processes through which infants are successful in eliciting responses from their peers, illustrating the presence of multiple pathways to achieving social competence with peers.     

ALL-BIAS DESIGNS FOR POLYNOMIAL SPLINE REGRESSION MODELS

Polynomial spline regression models of low degree have proved useful in modeling responses from designed experiments in science and engineering when simple polynomial models are inadequate. Where there is uncertainty in the number and location of the knots, or breakpoints, of the spline, then designs that minimize the systematic errors resulting from model misspecification may be appropriate. This paper gives a method for constructing such all‐bias designs for a single variable spline when the distinct knots in the assumed and true models come from some specified set. A class of designs is defined in terms of the inter‐knot intervals and sufficient conditions are obtained for a design within this class to be all‐bias under linear, quadratic and cubic spline models. An example of the construction of all‐bias designs is given.     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.