Assessing local influence for specific restricted likelihood: Application to factor analysis

In restricted statistical models, since the first derivatives of the likelihood displacement are often nonzero, the commonly adopted formulation for local influence analysis is not appropriate. However, there are two kinds of model restrictions in which the first derivatives of the likelihood displacement are still zero. General formulas for assessing local influence under these restrictions are derived and applied to factor analysis as the usually used restriction in factor analysis satisfies the conditions. Various influence schemes are introduced and a comparison to the influence function approach is discussed. It is also shown that local influence for factor analysis is invariant to the scale of the data and is independent of the rotation of the factor loadings. The authors are most grateful to the referees, the Associate Editor, and the Editor for helpful suggestions for improving the clarity of the paper.     

A monotonically convergent algorithm for orthogonal congruence rotation

Brokken has proposed a method for orthogonal rotation of one matrix such that its columns have a maximal sum of congruences with the columns of a target matrix. This method employs an algorithm for which convergence from every starting point is not guaranteed. In the present paper, an iterative majorization algorithm is proposed which is guaranteed to converge from every starting point. Specifically, it is proven that the function value converges monotonically, and that the difference between subsequent iterates converges to zero. In addition to the better convergence properties, another advantage of the present algorithm over Brokken's one is that it is easier to program. The algorithms are compared on 80 simulated data sets, and it turned out that the new algorithm performed well in all cases, whereas Brokken's algorithm failed in almost half the cases. The derivation of the algorithm is given in full detail because it involves a series of inequalities that can be of use to derive similar algorithms in different contexts.This research has been made possible by a fellowship from the Royal Netherlands Academy of Arts and Sciences to the first author. The authors are obliged to Willem J. Heiser and Jos M. F. ten Berge for useful comments on an earlier version of this paper.     

A model and algorithm for multidimensional scaling with external constraints on the distances

A method for externally constraining certain distances in multidimensional scaling configurations is introduced and illustrated. The approach defines an objective function which is a linear composite of the loss function of the point configurationX relative to the proximity dataP and the loss ofX relative to a pseudo-data matrixR. The matrixR is set up such that the side constraints to be imposed onX's distances are expressed by the relations amongR's numerical elements. One then uses a double-phase procedure with relative penalties on the loss components to generate a constrained solutionX. Various possibilities for constructing actual MDS algorithms are conceivable: the major classes are defined by the specification of metric or nonmetric loss for data and/or constraints, and by the various possibilities for partitioning the matricesP andR. Further generalizations are introduced by substitutingR by a set ofR matrices,R _i ,i=1, ...r, which opens the way for formulating overlapping constraints as, e.g., in patterns that are both row- and column-conditional at the same time.     

Matrix reorganization and dynamic programming: Applications to paired comparisons and unidimensional seriation

A recursive dynamic programming strategy is discussed for optimally reorganizing the rows and simultaneously the columns of ann ×n proximity matrix when the objective function measuring the adequacy of a reorganization has a fairly simple additive structure. A number of possible objective functions are mentioned along with several numerical examples using Thurstone's paired comparison data on the relative seriousness of crime. Finally, the optimization tasks we propose to attack with dynamic programming are placed in a broader theoretical context of what is typically referred to as the quadratic assignment problem and its extension to cubic assignment.Partial support for this research was provided by NIJ Grant 80-IJ-CX-0061.     

Navigation in multiobjective optimization methods

Building on previous work of the authors, this paper formally defines and reviews the first approach, referred to as navigation , towards a common understanding of search and decision‐making strategies to identify the most preferred solution among the Pareto set for a multiobjective optimization problem. In navigation methods, the decision maker interactively learns about the problem, whereas the decision support system learns about the preferences of the decision maker. This work introduces a detailed view on navigation leading to the identification of integral components and features. A number of different existing navigation methods are reviewed and characterized. Finally, an overview of applications involving navigation is given, and promising future research direction are discussed.     

癫痫的诊治与人文思想

癫痫是神经科常见的疾病之一,对于患者的学习、生活和工作均有不同程度影响。它的发病机制尚不十分清楚,主要是以药物治疗为主。在癫痫的诊断中要根据病情和患者的实际情况选择合适的检查;在癫痫的治疗中须按照最优化的医疗原则选择最佳的治疗方案。在治疗中要注意结合人文思想来提高癫痫的治疗效果。     

Use of a differential observing response to expand restricted stimulus control

This study extends previous work on the use of differential observing responses (DOR) to remediate atypically restricted stimulus control. A participant with autism had high matching-to-sample accuracy scores with printed words that had no letters in common (e.g., cat, lid, bug) but poor accuracy with words that had two letters in common (e.g., cat, can, car). In the DOR intervention, she matched the distinguishing letters of the overlapping words (e.g., t, n, r) immediately prior to matching the whole words. Accuracy scores improved, and accuracy remained high when DOR requirements were withdrawn.     

动态文本最优化呈现的眼动研究

采用2（呈现方式：平滑滚动引导式、RSVP）×5（呈现速度：120、240、360、480、600字/分）×3（窗口大小：5、10、15字）的多因素混合实验设计,运用EyelinkⅡ眼动仪对汉语动态文本阅读过程进行研究。结果发现,呈现速度较快（≥360字/分）时,与RSVP条件相比,被试在平滑滚动引导式条件下的平均注视时间短、注视次数多、眼跳距离小,阅读理解率高,且被试更偏爱此种呈现方式;呈现速度较慢（≤240字/分）时,两种呈现方式在平均注视时间和注视次数上没有差异。在平滑滚动引导式下,被试在三种窗口大小中各项指标上没有差异;在RSVP条件下,与5字窗口相比,大窗口（10字或15字）条件下平均注视时间更短。     

Undecidable Decisions: Rationality Limits and Decision-making Heuristics

In this article the theoretic evolution and the empirical-experimental efforts that have led to the affirmation of the bounded/procedural rationality paradigm are discussed. Moreover, the debate on supporters of the “optimization” approach and supporters of the “bounded/procedural rationality” approach is traced, highlighting the irreconcilability of these two approaches and, in retort, a solid defense against a merely “reductionist” attempt of the innovative context of the Simonian theory. Critically going over the debate on decision dynamics, it becomes clear how, due to the uncertain nature of rational processes, it is impossible to establish the decision-making best way. The imperfect character of individual choice is explained by how the decider identifies a solution that appears satisfying in that moment due to cognitive and temporal limits.