A robust regression technique using compound estimation

Least squares fitting of regression models is a widely used technique. The presence of outliers in the data can have an adverse effect on the method of least squares, resulting in a model that does not adequately fit to the bulk of the data. For this situation, robust regression techniques have been proposed as an improvement to the method of least squares. We propose a robust regression procedure that performs well relative to the current robust methods against a variety of dataset types. Evaluations are performed using datasets without outliers (testing efficiency), with a large percentage of outliers (testing breakdown), and with high leverage outliers (testing bounded influence). The datasets are based on 2-level factorial designs that include axial points to evaluate leverage effects. A Monte Carlo simulation approach is used to evaluate the estimating capability of the proposed procedure relative to several competing methods. We also provide an application to estimating costs for government satellites. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 125–139, 1998     

Computing the discounted return in markov and semi-markov chains

This paper addresses the problem of computing the expected discounted return in finite Markov and semi-Markov chains. The objective is to reveal insights into two questions. First, which iterative methods hold the most promise? Second, when are interative methods preferred to Gaussian elimination? A set of twenty-seven randomly generated problems is used to compare the performance of the methods considered. The observations that apply to the problems generated here are as follows: Gauss-Seidel is not preferred to Pre-Jacobi in general. However, if the matrix is reordered in a certain way and the author's row sum extrapolation is used, then Gauss-Seidel is preferred. Transforming a semi-Markov problem into a Markov one using a transformation that comes from Schweitzer does not yield improved performance. A method analogous to symmetric successive overrelaxation (SSOR) in numerical analysis yields improved performance, especially when the row-sum extrapolation is used only sparingly. This method is then compared to Gaussian elimination and is found to be superior for most of the problems generated.     

Threats and civil–military relations: explaining Singapore’s “trickle down” military innovation

This article explains why Singapore, despite its small size and semi-authoritarian regime, retains one of the best military forces in the Indo-Pacific. It unpacks Singapore’s ability to continuously innovate since the 1960s – technologically, organizationally, and conceptually – and even recently joined the Revolution in Military Affairs bandwagon. Drawing from the broader military innovation studies literature, this article argues evolutionary peacetime military innovation is more likely to occur in a state with a unified civil–military relation and whose military faces a high-level diverse set of threats. This argument explains how the civil–military fusion under the People’s Action Party-led government since Singapore’s founding moment has been providing coherent and consistent strategic guidance, political support, and financial capital, allowing the Singapore Armed Forces to continuously innovate in response to high levels and diversity of threats.     

Competitive Strategies against Continental Powers: The Geopolitics of Sino-Indian-American Relations

This article makes three arguments about the Sino-American competition, the Sino-Indian rivalry, and the US-India partnership. First, past maritime-continental rivalries suggest that China will pose a greater challenge to American interests as it confronts fewer threats on land, while the US may require continental allies to counter-balance China's rise. Second, whereas a Sino-Indian continental security dilemma could benefit the US by compelling China to invest in capabilities that do not threaten it, a Sino-Indian maritime security dilemma could have the opposite effect. Third, Washington should consider India as a prospective continental ally rather than a potential maritime partner.     

Economic design of X¯ control charts for two manufacturing process models

Control charts are widely used for process surveillance. The design of a control chart refers to the choice of sample size, the width of the control limits, and the interval between samples. Economic designs have been widely investigated and shown to be an effective method of determining control chart parameters. This article describes two different manufacturing process models to which the X¯ control chart is applied: The first model assumes that the process continues in operation while searches for the assignable cause are made, and the second assumes that the process must be shut down during the search. Economic models of the control chart for these two manufacturing process models are developed, and the sensitivity of the control chart parameters to the choice of model is explored. It is shown that the choice of the proper manufacturing process model is critical because selection of an inappropriate process model may result in significant economic penalties.     

Rethinking Stability in South Asia: India,Pakistan, and the Competition for Escalation Dominance

India and Pakistan are currently engaged in a competition for escalation dominance. While New Delhi is preparing for a limited conventional campaign against Pakistan, Islamabad is pursuing limited nuclear options to deter India. Together, these trends could increase the likelihood of nuclear conflict. India, for example, might conclude that it can launch an invasion without provoking a nuclear reprisal, while Pakistan might believe that it can employ nuclear weapons without triggering a nuclear exchange. Even if war can be avoided, these trends could eventually compel India to develop its own limited nuclear options in an effort to enhance deterrence and gain coercive leverage over Pakistan.