OPTIMAL SAFETY-STOCK INVESTMENT THROUGH SUBJECTIVE EVALUATION OF STOCKOUT COSTS

This paper solves the problem of setting safety stocks by combining a subjective evaluation of the stockout-cost function with the usual holding-cost function. The technique given in this paper for estimating a decision maker's (DM's) disvalue function for stockouts is robust in terms of the shapes permissible for this function and allows for uncertainty on the part of the DM in expressing his/her trade-offs. The estimation technique could be applied to situations other than the safety-stock problem. We provide an optimization routine for the safety-stock problem which is designed to operate in conjunction with the estimation technique. Safety-stock levels are arrived at iteratively.     

On the Use of Hierarchical Probabilistic Models for Characterizing and Managing Uncertainty in Risk/Safety Assessment

A general probabilistically-based approach is proposed for both cancer and noncancer risk/safety assessments. The familiar framework of the original ADI/RfD formulation is used, substituting in the numerator a benchmark dose derived from a hierarchical pharmacokinetic/pharmacodynamic model and in the denominator a unitary uncertainty factor derived from a hierarchical animal/average human/sensitive human model. The empirical probability distributions of the numerator and denominator can be combined to produce an empirical human-equivalent distribution for an animal-derived benchmark dose in external-exposure units.     

Sampling Richness and Qualitative Integrity: Challenges for Research With Families

Sampling is one of the most difficult and contentious aspects of qualitative research design. There are few guidelines for sampling decisions or for understanding saturation in qualitative family research. The authors frame the problematic of data quality in the selection of units of analysis and observation and consider how to enhance sample richness. They outline considerations for data quantity and sample size as well as case‐ and variable‐based approaches. With multiple examples from recent and classic studies to illustrate the consequences of sampling decisions, they explore links between saturation and validity. Finally, they encourage researchers to craft a coherent statement on qualitative integrity to demonstrate how their sampling decisions are rooted in epistemology, theory, and richness and quality of data.     

Upper Confidence Limits on Excess Risk for Quantitative Responses

The definition and observation of clear-cut adverse health effects for continuous (quantitative) responses, such as altered body weights or organ weights, are difficult propositions. Thus, methods of risk assessment commonly used for binary (quantal) toxic responses such as cancer are not directly applicable. In this paper, two methods for calculating upper confidence limits on excess risk for quantitative toxic effects are proposed, based on a particular definition of an adverse quantitative response. The methods are illustrated with data from a dose-response study, and their performance is evaluated with a Monte Carlo simulation study.     

A model for the assessment of static and dynamic factors in sexual offenders

A sample of 519 sexual offenders who were consecutive admissions to the Ontario Region of Correctional Service of Canada (CSC) were assessed with reference to a large series of variables thought to be related to sexual offending. We grouped these variables into five domains: criminality, social competence, sexual deviance, substance abuse and treatment readiness. We standardized scores on each of these domains to facilitate the calculation of total scores for each domain. We then performed a variety of analyses to determine whether these domains might constitute a reasonable model for the comprehensive evaluation of sexual offenders. Analyses indicated that overall the model received a moderate level of support.     

Experimental Design of Bioassays for Screening and Low Dose Extrapolation

Relatively high doses of chemicals generally are employed in animal bioassays to detect potential carcinogens with relatively small numbers of animals. The problem investigated here is the development of experimental designs which are effective for high to low dose extrapolation for tumor incidence as well as for screening (detecting) carcinogens. Several experimental designs are compared over a wide range of different dose response curves. Linear extrapolation is used below the experimental data range to establish an upper bound on carcinogenic risk at low doses. The goal is to find experimental designs which minimize the upper bound on low dose risk estimates (i.e., maximize the allowable dose for a given level of risk). The maximum tolerated dose (MTD) is employed for screening purposes. Among the designs investigated, experiments with doses at the MTD, 1/2 MTD, 1/4 MTD, and controls generally provide relatively good data for low dose extrapolation with relatively good power for detecting carcinogens. For this design, equal numbers of animals per dose level perform as well as unequal allocations.     

Portfolio optimization: New capabilities and future methods

Summary  This paper addresses the problem of portfolio selection in finance. In many cases, currently available software to compute the efficient frontier runs into difficulty in problems with more than about 600 securities. To proceed beyond this size, it is often necessary to modify the problem in which case there is typically a loss of information. In this paper, we discuss a computer capability that can exactly compute mean-variance efficient frontiers of problems with up to 2,000 securities in very reasonable time (even if a problem’s covariance matrix is 100% dense). The paper also discusses an augmentation to the theory of portfolio selection that allows multiple objectives (such as dividends, liquidity, social responsibility, amount invested in R&D, and so forth) to be incorporated into the portfolio selection process. In such problems, the efficient set is no longer a “frontier,” but is now best described as a “surface” with the interesting property that it is composed of platelets (like on the back of a turtle). Moreover, the computer capability that can compute the exact efficient frontier of a mean-variance problem with up to 2,000 securities also has, after additional coding, the ability to compute exactly all platelets of the efficient surface of a tri-criterion portfolio problem with up to 400 securities.

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Zusammenfassung  In dieser Arbeit stellen wir einen leistungsf?higen Rechenalgorithmus vor, um den effizienten Rand (die nichtdominierten Alternativen) von Portfolio-Auswahlproblemen in der Finanzierung zu bestimmen. Wir bezeichnen den Berechnungsalgorithmus, der in Java programmiert ist, mit MPQ (multi-parametric quadratic programming). MPQ weist gegenüber bisherigen Berechnungsverfahren eine Reihe von Vorteilen auf: Es kann für umfangreiche Anwendungsf?lle genutzt werden, ist durch passable Rechenzeiten charakterisiert und kann die Menge effizienter Alternativen in einem Bruchteil bisher üblicher Rechenzeiten bestimmen.