Adaptation over parametric families of symmetric linear estimators

This paper treats an abstract parametric family of symmetric linear estimators for the mean vector of a standard linear model. The estimator in this family that has smallest estimated quadratic risk is shown to attain, asymptotically, the smallest risk achievable over all candidate estimators in the family. The asymptotic analysis is carried out under a strong Gauss–Markov form of the linear model in which the dimension of the regression space tends to infinity. Leading examples to which the results apply include: (a) penalized least squares fits constrained by multiple, weighted, quadratic penalties; and (b) running, symmetrically weighted, means. In both instances, the weights define a parameter vector whose natural domain is a continuum.     

Arbeit und Leben in Organisationen 2008

Mitteilungen

Arbeit und Leben in Organisationen 2008 Anlage und Ergebnisse der Studie     

Least squares and shrinkage estimation under bimonotonicity constraints

In this paper we describe active set type algorithms for minimization of a smooth function under general order constraints, an important case being functions on the set of bimonotone r×s matrices. These algorithms can be used, for instance, to estimate a bimonotone regression function via least squares or (a smooth approximation of) least absolute deviations. Another application is shrinkage estimation in image denoising or, more generally, regression problems with two ordinal factors after representing the data in a suitable basis which is indexed by pairs (i,j)∈{1,…,r}×{1,…,s}. Various numerical examples illustrate our methods.     

The gradual decline of cooperation: Endgame effects in evolutionary game theory

The article provides an evolutionary analysis of a finitely iterated Prisoner's Dilemma. The backward induction reasoning for a breakdown of cooperation in this game is transformed to an evolutionary degradation effect. After the introduction of random variations in the strategies' population size, however, cyclical variations of cooperativeness may appear. A breakdown of cooperation is no longer inevitable. An analysis for all possible payoff relations in Prisoner's Dilemma matrices shows that only four qualitatively different dynamical flows can emerge.     

Theory and method in treatment evaluation

We outline a conceptual model of evaluation research that has both guided and flowed from our research on the process and outcome of treatment for alcohol abuse and for depression. The conceptual model encompasses three basic processes: the process of treatment selection, the process of treatment, and the process underlying the onset and course of the disorder or problem being treated. A theory guiding a program evaluation can focus on one or more of these processes, and findings from evaluations can contribute to the development of better theories of these processes. We discuss how theories can guide both experimental and naturalistic evaluations, as well as aid in the estimation of treatment effects with either type of design. We then consider the role of theory and method in exploring patient-treatment matching. Finally, we discuss the implications of theory-guidance for the utility of evaluations—particularly the utility for evaluation researchers.     

Weighted Median of the Data in Solving Least Absolute Deviations Problems

We consider the weighted median problem for a given set of data and analyze its main properties. As an illustration, an efficient method for searching for a weighted Least Absolute Deviations (LAD)-line is given, which is used as the basis for solving various linear and nonlinear LAD-problems occurring in applications. Our method is illustrated by an example of hourly natural gas consumption forecast.     

Principles of children's gynecology in Czechoslovakia

This paper documents specific aspects of sex and eroticism as well as related aspects of social development in a small group of postpubertal male patients diagnosed as having hypopituitarism secondarily to the surgical removal of a pituitary tumor. The data include information about erection, ejaculation, masturbation, erotic imagery and intercourse, as well as dating, socializing and falling in love. Problems of case management are also discussed.     

The DYNAMO-HIA Model: An Efficient Implementation of a Risk Factor/Chronic Disease Markov Model for Use in Health Impact Assessment (HIA)

In Health Impact Assessment (HIA), or priority-setting for health policy, effects of risk factors (exposures) on health need to be modeled, such as with a Markov model, in which exposure influences mortality and disease incidence rates. Because many risk factors are related to a variety of chronic diseases, these Markov models potentially contain a large number of states (risk factor and disease combinations), providing a challenge both technically (keeping down execution time and memory use) and practically (estimating the model parameters and retaining transparency). To meet this challenge, we propose an approach that combines micro-simulation of the exposure information with macro-simulation of the diseases and survival. This approach allows users to simulate exposure in detail while avoiding the need for large simulated populations because of the relative rareness of chronic disease events. Further efficiency is gained by splitting the disease state space into smaller spaces, each of which contains a cluster of diseases that is independent of the other clusters. The challenge of feasible input data requirements is met by including parameter calculation routines, which use marginal population data to estimate the transitions between states. As an illustration, we present the recently developed model DYNAMO-HIA (DYNAMIC MODEL for Health Impact Assessment) that implements this approach.