On control charts for monitoring the variance of a time series

In this paper we derive control charts for the variance of a Gaussian process using the likelihood ratio approach, the generalized likelihood ratio approach, the sequential probability ratio method and a generalized sequential probability ratio procedure, the Shiryaev–Roberts procedure and a generalized modified Shiryaev–Roberts approach. Recursive presentations for the calculation of the control statistics are given for autoregressive processes of order 1. In an extensive simulation study these schemes are compared with existing control charts for the variance. In order to asses the performance of the schemes both the average run length and the average delay are used.     

Bayesian networks for sex-related homicides: structure learning and prediction

Sex-related homicides tend to arouse wide media coverage and thus raise the urgency to find the responsible offender. However, due to the low frequency of such crimes, domain knowledge lacks completeness. We have therefore accumulated a large data-set and apply several structural learning algorithms to the data in order to combine their results into a single general graphic model. The graphical model broadly presents a distinction between an offender and a situation-driven crime. A situation-driven crime may be characterised by, amongst others, an offender lacking preparation and typically attacking a known victim in familiar surroundings. On the other hand, offender-driven crimes may be identified by the high level of forensic awareness demonstrated by the offender and the sophisticated measures applied to control the victim. The prediction performance of the graphical model is evaluated via a model averaging approach on the outcome variable offender's age. The combined graph undercuts the error rate of the single algorithms and an appropriate threshold results in an error rate of less than 10%, which describes a promising level for an actual implementation by the police.     

Monotony relations between distribution functions and their application to experimental design

In a linear regression model an estimator of the unknown coefficients is considered which, in special cases, includes the least squares estimator. In the ease of stable symmetric error distribution and by means of a certain monotony relation between distribution functions optimality of this estimator is proved and the designing problem is investigated. A robustness property of optimal designs against the designing criterion and some conclusions are given concerning the least squares estimator in the case of G- and C-optimality.     

Simulation experiments of resource-allocation decisions in two-level organizations

A model two-level organization consisting of headquarters and two divisions is considered. Headquarters is faced with a decision-problem: to allocate certain scarce resources in a “good” way between the two divisions. Three different methods that can be used to reach that allocation decision are studied. Those three methods are (1) to simply divide the resources equally between the divisions; (2) a method based on an iterative pricing mechanism; and (3) an adaptation of the Dantizig-Wolfe decomposition algorithm. The paper investigates, by means of a set of simulation experiments, the effects of these methods on organizational performance, both as regards overall payoff and divisional payoff. With respect to divisional payoff, a divisional payoff-structure is postulated, and it is examined whether divisional payoff can be improved through “cheating.”     

Inferring decision strategies from clickstreams in decision support systems: a new process-tracing approach using state machines

Webstores can easily gather large amounts of consumer data, including clicks on single elements of the user interface, navigation patterns, user profile data, and search texts. Such clickstream data are both interesting to merchandisers as well as to researchers in the field of decision-making behavior, because they describe consumer decision-behavior on websites. This paper introduces an approach that infers decision-behavior from clickstream data. The approach observes clicks on elements of a decision-support-system and triggers a set of state-machines for each click. Each state-machine represents a particular decision-strategy which a user can follow. The approach returns a set of decision strategies that best explain the observed click-behavior of a user. Results of two experiments show that the algorithm infers strategies accurately. In the first experiment, the approach correctly infers most of the pre-defined decision-strategies. The second study analyzes the behavior of thirty-eight respondents and finds that the inferred mix of decision-strategies fits well the behavior described in the literature to date. Results show that using decision-support-systems on a web site and observing the user’s click-behavior make it possible to infer a specific decision strategy. The proposed method is general enough to be easily applied to both research and real-world settings, along with other decision-support-systems and strategies.     

Sequential estimation for a family of counting processes in the nuisance parameter case

The paper deals with the problem of sequential estimation for stochastic processes in the presence of a nuisance parameter. Using the approach to estimation through estimating equations, optimum estimating functions based on a random observation time are investigated in some models for processes appearing in reliability systems theory.     

The Multiple Outlier Problem in Time Series Analysis

In this paper we consider the multiple outlier problem in time series analysis. The underlying undisturbed time series is assumed to be an autoregressive process. The location of the suspicious values is supposed to be known. We introduce conditional least squares estimators for the parameters. The estimates are shown to be strongly consistent. Using similar arguments as in the theory of linear models, we get a test statistic for the general linear hypothesis. Its asymptotic distribution is derived.     

Occupational and Economic Mobility and Social Integration of Mediterranean Migrants in Germany

Foreigners of Mediterranean immigrant origin still occupy the lowerpositions in the German labour market. The employment profile is clearlydifferent from that of German wage earners and salaried employees. Resultsfrom the German Socio-Economic Panel Study show that 60% of this foreignpopulation was employed as unskilled or semi-skilled workers in 1993. Between1984 and 1993 their occupational mobility was relatively low. The situationof the second generation has clearly improved. To a small degree they evenfound access to attractive jobs in the service sector. But compared withGermans of the same age group their occupational success is limited. Thesocial situation of foreigners is characterised by increasing segregation.     

人工智能的未来：“慈爱的机器”还是“交际的工具”

人们对于人工智能的未来有很多设想，其中有两种设想很具有代表性。所谓“慈爱的机器”是一种技术乌托邦式的未来幻想，一种仁慈的技术统治维护着全面的和谐。人工智能作为一种“交际的工具”，对未来的想象也勾勒出了一个平衡的社会，但它颠倒了(前一种设想)影响的顺序:一个交际性的社会为交际行为塑造了相关的技术。但事实是，没有任何一个程序能够满足为所有人都能够接受的普遍规则。人类不需要担心人工智能会变成一个邪恶的还是仁慈的东西，因为人工智能技术原则上不具备邪恶和仁慈的能力。但人工智能可以侵入人类的自主性，以致达到一种无法容忍的程度。     

Industrial Relations in West Germany, 1980-1987

ABSTRACT: The paper describes the structure and state of industrial relations in the Federal Republic of Germany and discusses perspectives and problems of their future development. Its composition follows the syllabus of an internationally comparative research project.