Optimal scaling of Metropolis algorithms: Heading toward general target distributions

The authors provide an overview of optimal scaling results for the Metropolis algorithm with Gaussian proposal distribution. They address in more depth the case of high‐dimensional target distributions formed of independent, but not identically distributed components. They attempt to give an intuitive explanation as to why the well‐known optimal acceptance rate of 0.234 is not always suitable. They show how to find the asymptotically optimal acceptance rate when needed, and they explain why it is sometimes necessary to turn to inhomogeneous proposal distributions. Their results are illustrated with a simple example.     

Some results on optimality in models with heteroscedastic errors from partial optimum designs

This paper studies optimum designs for linear models when the errors are heteroscedastic. Sufficient conditions are given in order to obtainD-, A- andE-optimum designs for a complete regression model from partial optimum designs for some sub-parameters. A result about optimality for a complete model from the optimality for the submodels is included. Supported by Junta de Andalucía, research group FQM244.     

A “brer rabbit” case for reverse mandated benefits

Reverse mandated benefits is a government-mandated policy that requires employees to provide their employers with benefits that workers would not provide otherwise. Of course, only those benefits would be mandated that are worth more to employers than they cost, as determined by political authorities. My case for such a policy argues that it is at least as sensible as policies mandating that employers provide benefits to their employees that would not be provided otherwise.     

Intertemporal choice under timing risk: An experimental approach

This paper investigates how individuals evaluate delayed outcomes with risky realization times. Under the discounted expected utility (DEU) model, such evaluations depend only on intertemporal preferences. We obtain several testable hypotheses using the DEU model as a benchmark and test these hypotheses in three experiments. In general, our results show that the DEU model is a poor predictor of intertemporal choice behavior under timing risk. We found that individuals are averse to timing risk and that they evaluate timing lotteries in a rank-dependent fashion. The main driver of timing risk aversion is nothing but probabilistic risk aversion that stems from the nonlinear treatment of probabilities.     

Equity Challenges for the Early Childhood Curriculum

Curriculum documents from the USA, UK and Australia show remarkable harmony on the need for a developmentally-based curriculum in producing quality early childhood programmes. This paper uses a detailed discussion of a grass roots level research project in Australia to explore the contention that a curriculum built solely on these principles and the practices that develop from them is likely to be sexist. Several aspects of the curriculum that need rethinking in relation to gender equity goals are identified.     

Beheimatungsprozesse begleiten — ein Werkstattbericht

Supporting processes of belonging in supervision and coachingThe contemporary employee has to cope with frequent changes. Not only does he lose his familiar environment, he also has to find ways to familiarize himself with new places and to develop a fresh sense of belonging. This process can be understood and facilitated by interpreting the German concept of “Heimat“ as something we have to create ourselves. First experiences demonstrate the usefulness of this approach in coaching processes.     

Expected sample moments of concomitants of selected order statistics

In this paper, the task of determining expected values of sample moments, where the sample members have been selected based on noisy information, is considered. This task is a recurring problem in the theory of evolution strategies. Exact expressions for expected values of sums of products of concomitants of selected order statistics are derived. Then, using Edgeworth and Cornish-Fisher approximations, explicit results that depend on coefficients that can be determined numerically are obtained. While the results are exact only for normal populations, it is shown experimentally that including skewness and kurtosis in the calculations can yield greatly improved results for other distributions.     

How bad can a voting location be

Two questions concerning the location of a single facility by a voting process are investigated for transportation networks:

- What is the maximum number of customers located on the network preferring some rival point over a voting solution?

- How does the average distance of the customers to the facility increase when a voting location instead of a Weber location is chosen for the facility?

Complete answers are given for general networks and for certain planar networks, viz., the so-called generalized cacti.