Statistical inference for Sobol pick-freeze Monte Carlo method

Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variability of a quantity of interest (output of the model). One of the statistical tools used to quantify the influence of each input variable on the output is the Sobol sensitivity index. We consider the statistical estimation of this index from a finite sample of model outputs. We study asymptotic and non-asymptotic properties of two estimators of Sobol indices. These properties are applied to significance tests and estimation by confidence intervals.     

A Generic Model of Long Term Care for Social Work Education

Abstract

With the “graying” of America and the increasing life expectancy for the developmentally disabled, there is an increasing demand for long-term care (LTC). As in the past, provision of this care will depend heavily on families. Professional social work can expect an increased role in facilitating the balance of LTC resources. As this role evolves, social work educators may develop anticipatory responses by incorporating a generic but comprehensive framework of LTC in social work curricula. Such a framework is presented in this paper. It is neither age- nor etiology-specific; it is appropriate for use with the developmentally disabled, the frail elderly, or any other population in need of LTC.     

Image reconstruction by adaptive bayesian classification with a locally proportional prior

This paper concerns the problem of reconstructing images from noisy data by means of Bayesian classification methods. In Klein and Press, 1992, the authors presented a method for reconstructing images called Adaptive Bayesian Classification (ABC). The ABC procedure was shown to preform very well in simulation experiments. The ABC procedure was multistaged; moreover, it involved selecting a prior at Stage n that was the posterior at Stage n - 1. In this paper the authors show that we can improve upon ABC for some problems by modifying the way we take the prior at each stage. The new proposal is to take the prior for the pixel label at each stage as proportional to the number of pixels with that label in a small neighborhood of the pixel. The ABC procedure with a locally proportional prior (ABC/LPP) tends to improve upon the ABC procedure for some problems because the prior in the iterative portion of ABC/LPP is contextual, while that in ABC in non- contextual.     

Approximate E-optimal designs for the model of spring balance weighing with a constant bias

The present paper analyzes the linear regression model with a nonzero intercept term on the vertices of a d-dimensional unit cube. This setting may be interpreted as a model of weighing d objects on a spring balance with a constant bias. We give analytic formulas for E-optimal designs, as well as their minimal efficiencies under the class of all orthogonally invariant optimality criteria, proving the criterion-robustness of the E-optimal designs. We also discuss the D- and A-optimal designs for this model.     

The sexual experience and marital adjustment of genitally circumcised and infibulated females in the Sudan

In a study conducted over a 5‐year period, the author interviewed over 300 Sudanese women and 100 Sudanese men on the sexual experience of circumcised and infibulated women. Sudanese circumcision involves excision of the clitoris, the labia minora and the inner layers of the labia majora, and fusion or infibulation of the bilateral wound. The findings of this study indicate that sexual desire, pleasure, and orgasm are experienced by the majority of women who have been subjected to this extreme sexual mutilation, in spite of their also being culturally bound to hide these experiences. These findings also seriously question the importance of the clitoris as an organ that must be stimulated in order to produce female orgasm, as is often maintained in Western sexological literature.     

The Use of Adjunct Faculty: An Exploratory Study of Eight Social Work Programs

This pilot study of the practice of employing social work practitioners as adjunct faculty analyzes the results of questionnaires returned from 6 deans/directors, 43 adjunct faculty, and 175 students at 8 U.S. institutions offering BSW and/or MSW programs. The responses covered the teaching effectiveness of adjunct faculty (in 1992–93), their reasons for teaching, the support received from and expectations of the programs, and various pros and cons surrounding their employment. Among the findings: students regard adjunct faculty as somewhat less effective teachers than full-time faculty, but appreciate their expertise on contemporary or specialized practices; administrators appreciate the financial benefits and flexibility associated with adjunct instruction; and the adjuncts themselves appreciate affiliation with academic programs.     

The Robustness of Several Estimators of the Survivorship Function with Randomly Censored Data

The problem of estimating the survivorship function, R(t) = P(T > t), arises frequently in both engineering and biomedical sciences. In many applications the data one sees are censored due to the occurrence of some competing cause of failure such as withdrawal from the study, failure from some cause not under study, etc. In the biomedical sciences the distribution free estimator suggested by Kaplan and Meier (JASA 1958) is routinely used, while in the engineering sciences a parametric approach is more commonly used. In this report we study the efficiency of these two techniques when a particular parametric model such as the exponential, Weibull, normal, log normal, exponential power, Pareto, Gompertz, gamma, or bathtub shaped hazard distribution is assumed under a variety of censoring schemes and underlying failure models. We conclude that in most cases the parametric estimators outperform the distribution free estimator. The results are particularly striking if the Weibull forms of these estimators are used routinely.     

Skewness by Splitting the Scale Parameter

This article describes a recursive nonparametric estimation for the local partial first derivative of an arbitrary function satisfied some regularity conditions and establishes its consistency and asymptotic normality under the assumption of strong mixing sequence. The proposed estimator is a variable window width version of the Watson-Nadaraya type of derivative estimator. The window width varied as more data points become available enables a recursive algorithm that reduce computational complexity from order N ³ normally required by batch methods for kernel regression to order N ². This approach is computationally simple and attractive from practical viewpoint especially when the situation call for frequent updating of first derivative estimates. For example, maintaining a delta-hedged position of a portfolio of equities with index options is one of many applications of such estimation.     

Weibull accelerated life tests when there are competing causes of failure

Accelerated life testing of a product under more severe than normal conditions is commonly used to reduce test time and costs. Data collected at such accelerated conditions are used to obtain estimates of the parameters of a stress translation function. This function is then used to make inference about the product's life under normal operating conditions. We consider the problem of accelerated life tests when the product of interest is a p component series system. Each of the components is assumed to have an independent Weibull time to failure distribution with different shape parameters and different scale parameters which are increasing functions stress. A general model i s used for the scale parameter includes the standard engineering models as special This model also has an appealing biological interpretation