Consistency of the bootstrap for the ransformed two-sample t-test

A method of bootstrapping the two-sample t-test after a Box-Cox transformation is proposed. The procedure is shown to be consistent and asymptotically as efficient as the non-bootstrapped Box-Cox t-test. Because the bootstrap samples are drawn without the assumption of the same distributional shapes,the procedure may be more robust against violation of this assumption. Simulation results support this conjecture.     

Random quotients and robust estimation

This paper compares the tail-heaviness of certain random quotients in terms of the asymptotic relative efficiences of the sample median to a large class of estimators containing the mean, trimmed mean and Huber's M-estimator. The random quotients are generalizations of the "Normalllndependent" distributions and include the Student's t, contaminated normal, double exponential and slash distributions.     

Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.     

Ocean Protection in Times of Intense Change

The ocean represents about 71％ of the surface of the earth. This alone shows that the ocean matters, and we should protect it. The ocean is the habitat of many ...     

Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic

With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUV's technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.     

Application of box-cox transformations to discrimination for the two-class problem

The performance of Box-Cox power transformations in classification using Hinkley's (1975) method is studied. Misclassification probabilities before and after transformation are compared. It is found that the use of Box-Cox transformations can sometimes substantially reduce the error probabilities. Estimates of error probabilities are obtained and certain properties are derived. Examples for a number of distributions are given.     

Physical inactivity and working hour inflexibility: evidence from a U.S. sample of older men

Lack of time is the most frequently reported reason for lack of exercise. This study examines how restriction on the number of working hours affects individuals’ exercise decision. A structural model is constructed to describe the simultaneous decisions of employment and physical activity in the presence of working hour restriction. Using data from the 1992 Health and Retirement Study, this study finds that the working hour restriction is partly responsible for the physical inactivity among older American workers. When the working hour restriction is binding from below, an increase in the number of hours required on the job considerably reduces the probability of engaging in frequent exercise. The results imply that partial relaxation of working hour restrictions may be considered to promote frequent exercise.

Estimating Mixing Densities in Exponential Family Models for Discrete Variables

This paper is concerned with estimating a mixing density g using a random sample from the mixture distribution f(x)=∫f x | θ)g(θ)dθ where f(· | θ) is a known discrete exponen tial family of density functions. Recently two techniques for estimating g have been proposed. The first uses Fourier analysis and the method of kernels and the second uses orthogonal polynomials. It is known that the first technique is capable of yielding estimators that achieve (or almost achieve) the minimax convergence rate. We show that this is true for the technique based on orthogonal polynomials as well. The practical implementation of these estimators is also addressed. Computer experiments indicate that the kernel estimators give somewhat disappoint ing finite sample results. However, the orthogonal polynomial estimators appear to do much better. To improve on the finite sample performance of the orthogonal polynomial estimators, a way of estimating the optimal truncation parameter is proposed. The resultant estimators retain the convergence rates of the previous estimators and a Monte Carlo finite sample study reveals that they perform well relative to the ones based on the optimal truncation parameter.