Optimal bounded influence regression and scale m-estimators in the context of experimental desing

The problem of simultaneous robust estimation of regression and scale parameters in the linear regression model is studied in the context of experimental design. Optimal M-estimates are given for a modified optimization problem of minimizing the asymptotic variances under bounded influence functions. This is done by reducing the multidimensional regression problem to the problem of estimating one-dimensional location and scale. For the location-scale case two subfamilies of optimal score functions are described in detail along with comparisons of the asymptotic variances and gross-error-sensitivities of the corresponding M-estimators. It turns out that, even for small gross-error-sensitivities, one of the subfamilies provides variances which are close to those of the nonrobust maximum likelihood estimators.     

On Combining Information in Generally Balanced Nested Block Designs

Explicit formulae for analyzing an experiment carried out in a nested block design having the general balance property of some desirable pattern are presented. They follow from a randomization-derived mixed model, decomposed into stratum submodels. Attention is confined here to the combined analysis allowing the information from different strata to be joined together. This article is an extension of some results presented in Caliński and Kageyama (2000 Caliński , T. , Kageyama , S. ( 2000 ). Block Designs: A Randomization Approach, vol. I: Analysis . Lecture Notes in Statistics , vol. 150. New York : Springer .[Crossref] , [Google Scholar]), where the theory underlying the considered analysis is given.     

A Comparison of Some Tests for Determining the Number of Nonzero Canonical Correlations

When considering the relationships between two sets of variates, the number of nonzero population canonical correlations may be called the dimensionality. In the literature, several tests for dimensionality in the canonical correlation analysis are known. A comparison of seven sequential test procedures is presented, using results from some simulation study. The tests are compared with regard to the relative frequencies of underestimation, correct estimation, and overestimation of the true dimensionality. Some conclusions from the simulation results are drawn.     

Mental fatigue at work and pain perception

The object of this study was to determine whether mental fatigue connected with high and low stimulation at work can affect the subjects' perception of pain. Two groups of female visual display unit operators were studied: the first group performed tasks involving high levels of stimulation, while the second group performed tasks involving low levels of stimulation. The results show that mental fatigue due to a high level of stimulation causes an increase in pain ratings, while the mental fatigue due to low stimulation level causes a decrease in pain ratings.     

Fréchet differentiability in statistical inference for time series

It is shown how the method of Fréchet differentiability can simplify the asymptotic derivations in an important range of robust inferential problems for stationary and related time series models. The uniform root-n consistency of the empirical distribution function for the Cramer von Mises norm under a weak mixing condition is indicated. Various regularity conditions naturally implemented and leading to the differentiability are discussed. A simulation study supplementing the theoretical discussion is included.     

Dispositional Factors Affecting Choices Surrounding the Purchase of Insurance and the Taking of Mitigating Measures Against Flooding

This research investigated the role of dispositional factors in decisions to purchase insurance and to take mitigating measures against flooding. Two dispositional factors—risk aversion in the domain of losses and time discounting rate—were found to be predictors of the decision to acquire flood insurance. The observation of a relationship between experiment-based risk attitudes and the decision to insure oneself against flooding replicates a finding of Petrolia et al. The finding that impatience negatively impacts decisions to take out insurance against flooding is novel. However, support was not found for analogous hypotheses concerning relationships between the two dispositional variables and decisions to take mitigating measures. Evidently, factors other than individual risk aversion and time discounting rate play a crucial role in this behavior.     

Selection of supply portfolio under disruption risks

This paper deals with the optimal selection of supply portfolio in a make-to-order environment in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order to minimize total cost and mitigate the impact of disruption risks. The selection of suppliers and allocation of orders is based on price and quality of purchased parts and reliability of delivery. The two types of disruption scenarios are considered: scenarios with independent local disruptions of each supplier and scenarios with local and global disruptions that may result in all suppliers disruption simultaneously. The problem is formulated as a single- or bi-objective mixed integer program and a value-at-risk and conditional value-at-risk approach is applied to control the risk of supply disruptions. The proposed portfolio approach is capable of optimizing the supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.