A hierarchical modelling approach for measuring reliability of and agreement between two types of magnetic field dosimeter

Summary.  The paper describes how to use hierarchical models to assess the reliability of and agreement between two or more types of measurement device. The idea is illustrated by fitting a linear model with nested random effects to a set of data that was obtained from the calibration of two samples of extremely low frequency magnetic field meters. The paper focuses on the formulation of a suitable model that accounts for the various aspects of the calibration protocol and the subsequent interpretation of the parameter estimates. The approach is very flexible and can easily be tuned to the various needs arising in the measurement agreement framework. It can be seen as an extension of the common practice of using a one-way random-effects model to retrieve a measure of agreement.     

Balanced Asymmetrical Nearly Orthogonal Designs for first and second order effect estimation

A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interaction estimability requirements with a number of runs as small as possible, is proposed in this paper. The method, based on a heuristic procedure, uses a new optimality criterion formulated here. The proposed method demonstrates efficiency in terms of searching time and optimality of the attained designs. A complete collection of such asymmetrical designs with two- and three-level factors is available. A technological application is also presented.     

Common Coding of Observation and Execution of Action in 9‐Month‐Old Infants

Do 9‐month‐old infants motorically simulate actions they perceive others perform? Two experiments tested whether action observation, like overt reaching, is sufficient to elicit the Piagetian A‐not‐B error. Infants recovered a toy hidden at location A or observed an experimenter recover the toy. After the toy was hidden at location B, infants in both conditions perseverated in reaching to A, demonstrating that active search by the infant is not necessary for the A‐not‐B error. Consistent with prior research, infants displayed an ipsilateral bias when reaching, the so‐called mysterious midline barrier. A similar ipsilateral bias was also observed depending on the manner in which the experimenter reached; infants perseverated following observation of ipsi‐ but not contralateral reaches by the experimenter. Thus, infants perseverated only following observation of actions they themselves were able to perform, suggesting that they coded others' actions in terms of motor simulation.     

A default Bayesian procedure for the generalized Pareto distribution

The generalized Pareto distribution is used to model the exceedances over a threshold in a number of fields, including the analysis of environmental extreme events and financial data analysis. We use this model in a default Bayesian framework where no prior information is available on unknown model parameters. Using a large simulation study, we compare the performance of our posterior estimations of parameters with other methods proposed in the literature. We show that our procedure also allows to make inferences in other quantities of interest in extreme value analysis without asymptotic arguments. We apply the proposed methodology to a real data set.     

Learning and interaction in groups with computers: when do ability and gender matter?

In the research reported in this article, we attempt to identify the background and process factors influencing the effectiveness of groupwork with computers in terms of mathematics learning. The research used a multi-site case study design in six schools and involved eight groups of six mixed-sex, mixed-ability pupils (aged 9–12) undertaking three research tasks – two using Logo and one a database. Our findings suggest that, contrary to other recent research, the pupil characteristics of gender and ability have no direct influence on progress in group tasks with computers. However, status effects – pupils' perceptions of gender and ability – do have an effect on the functioning of the group, which in turn can impede progress for all pupils concerned.     

Reinforced urns and the subdistribution beta‐Stacy process prior for competing risks analysis

In this paper, we introduce the subdistribution beta‐Stacy process, a novel Bayesian nonparametric process prior for subdistribution functions useful for the analysis of competing risks data. In particular, we (i) characterize this process from a predictive perspective by means of an urn model with reinforcement, (ii) show that it is conjugate with respect to right‐censored data, and (iii) highlight its relations with other prior processes for competing risks data. Additionally, we consider the subdistribution beta‐Stacy process prior in a nonparametric regression model for competing risks data, which, contrary to most others available in the literature, is not based on the proportional hazards assumption.     

Sub-optimal investment for insurers

Abstract

We consider the investment problem for a non-life insurance company seeking to minimize the ruin probability. Its reserve is described by a perturbed risk process possibly correlated with the financial market. Assuming exponential claim size, the Hamilton-Jacobi-Bellman equation reduces to a first order nonlinear ordinary differential equation, which seems hard to solve explicitly. We study the qualitative behavior of its solution and determine the Cramér-Lundberg approximation. Moreover, our approach enables to find very naturally that the optimal investment strategy is not constant. Then, we analyze how much the company looses by adopting sub-optimal constant (amount) investment strategies.     

The Dimensions of Agricultural Diversification: A Spatial Analysis of Italian Municipalities

Diversification in agriculture could ensure the survival of farming by broadening the income base of farms and encouraging agricultural sustainability. The diversification of on-farm activities may depend on socioeconomic and environmental characteristics. Although multifunctionality is a hotly debated topic, few papers have focused on the farm characteristics that influence diversification and none have focused on the influence of the spatial pattern. This paper examines the relationship between farm characteristics and the adoption of a specific type of diversification. An econometric model is presented that uses a spatial autoregressive lag model at the municipal scale. The results demonstrate that the activation of each diversification dimension is influenced by both internal and external factors, encompassing farmers’ characteristics, the farm structure, and territorial features, including regional and spatial patterns. Deepening is mainly influenced by the farmer’s age, education, and the presence of small and labor-intensive farms. The key factors for broadening diversification are the presence of small farms and farms with mixed production (breeding and crop cultivation). Regrounding is most affected by the labor-intensive farms in the area and the farms with mixed production.     

A class of neutral to the right priors induced by superposition of beta processes

A random distribution function on the positive real line which belongs to the class of neutral to the right priors is defined. It corresponds to the superposition of independent beta processes at the cumulative hazard level. The definition is constructive and starts with a discrete time process with random probability masses obtained from suitably defined products of independent beta random variables. The continuous time version is derived as the corresponding infinitesimal weak limit and is described in terms of completely random measures. It takes the interpretation of the survival distribution resulting from independent competing failure times. We discuss prior specification and illustrate posterior inference on a real data example.