The power of surrogate data testing with respect to non-stationarity

Surrogate data testing is a method frequently applied to evaluate the results of nonlinear time series analysis. Since the null hypothesis tested against is a linear, gaussian, stationary stochastic process a positive outcome may not only result from an underlying nonlinear or even chaotic system, but also from e.g. a non-stationary linear one. We investigate the power of the test against non-stationarity.Comment: 4 pages, 4 figures, to appear in PR

Actual Test Coverage for Embedded Systems

Testing embedded systems is inherently incomplete; no test suite will ever be able to test all possible usage scenarios. Therefore, in the past decades many coverage measures have been developed. These measures denote the portion of a system that is tested, that way providing a quality criterion for test suites. Formulating coverage criteria is not an easy task. The measures provided in the literature are consequently almost all very trivial and syntax-dependent. Well-known examples are statement and path coverage in white-box testing, and state and transition coverage in black-box testing. The complexity of designing coverage measures for embedded systems is contained in the highly dynamic behaviour of such systems, which is state-dependent and subject to many interleavings. In this talk we introduce a framework on actual test coverage. This measure denotes the number of faults actually shown present or absent. Our framework contains a method to evaluate the actual coverage of a given set of test suite executions after testing has taken place, providing a means to express the quality of a testing process. It also contains a method to predict the actual coverage a certain number of executions will yield, providing a means to select the best test suite. Both the evaluation afterwards and the prediction in advance are quite efficient, making it feasible to implement the theory in a tool and use it in a practical context

The effects of win-win conditions on revenue-sharing contracts

This paper studies revenue-sharing contracts in distribution chains in the presence of win-win conditions. Revenue-sharing contracts are a mechanism to coordinate the firms in a distribution chain. Under these contracts the retailer shares its revenue with the supplier in exchange for a lower wholesale price. The win-win conditions are natural conditions requiring that the profit of any firm may not decrease after implementing the revenue-sharing contract. If these conditions are not met, that is, if at least one firm is confronted with decreased profits, the firms will not agree upon signing the contract and the revenue-sharing contract will not be implemented. We show that the win-win conditions result in a smaller range of contracts being offered by the supplier. More important, in case of multiple competing retailers there may be no revenue-sharing contract satisfying these conditions. Hence, in the presence of win-win conditions revenue-sharing contracts are not suitable for distribution chains with a supplier and multiple competing retailers. For these chains we present a simple alternative coordination mechanism that coordinates the chain and satisfies all win-win conditions. \u

A coordination mechanism with fair cost allocation for divergent multi-echelon inventory systems

This paper is concerned with the coordination of inventory control in divergent multiechelon inventory systems under periodic review and decentralized control. All the installations track echelon inventories. Under decentralized control the installations will decide upon replenishment policies that minimize their individual inventory costs. In general these policies do not coincide with the optimal policies of the system under centralized control. Hence, the total cost under decentralized control is larger than under centralized control.\ud To remove this cost inefficiency, a simple coordination mechanism is presented that is initiated by the most downstream installations. The upstream installation increases its base stock level while the downstream installation compensates the upstream one for increased costs and provides it with additional side payments. We show that this mechanism coordinates the system; the global optimal policy of the system is the unique Nash equilibrium of the corresponding strategic game. Furthermore, the mechanism results in a fair allocation of the costs; all installations enjoy cost savings

Parameter estimation in nonlinear stochastic differential equations

We discuss the problem of parameter estimation in nonlinear stochastic differential equations based on sampled time series. A central message from the theory of integrating stochastic differential equations is that there exists in general two time scales, i.e. that of integrating these equations and that of sampling. We argue that therefore maximum likelihood estimation is computational extremely expensive. We discuss the relation between maximum likelihood and quasi maximum likelihood estimation. In a simulation study, we compare the quasi maximum likelihood method with an approach for parameter estimation in nonlinear stochastic differential equations that disregards the existence of the two time scales.Comment: in press: Chaos, Solitons & Fractal

The Compromise Value for Cooperative Games with Random Payoffs

AMS classification: 90D12;cooperative games

Supermarkets, Modern Supply Chains, and the Changing Food Policy Agenda

There is great interest among policy makers in how to influence the behavior of supermarkets in ways that serve the interests of important groups in society, especially small farmers and the owners of traditional, small-scale food wholesale and retail facilities. Two broader issues are also important: (1) finding a way for food prices to “internalize” the full environmental costs of production and marketing; and (2) finding a way for supermarkets to be part of the solution, rather than part of the problem, to the health problems generated by an “affluent” diet and lifestyle. There are concerns over the growing concentration in global food retailing and the potential market power that concentration implies. But the evidence of fierce competition at the retail level, and the high contestability for food consumers’ dollars, have kept this issue in the background. The ultimate impact of supermarkets in developing countries will be on the level and distribution of improved welfare for consumers. What happens to small farmers, traditional traders and mom-and-pop shops will be factors in both the size of welfare gains and their distribution, but many other factors will also come into play. Our judgment on the impact of the supermarket revolution must incorporate all of those factors. This paper places the supermarket debate in the broader evolution of food policy analysis, which is a framework for integrating household, market, macro and trade issues as they affect hunger and poverty. Increasingly, supermarkets provide the institutional linkages across these issues.Food policy; agricultural diversification; structural transformation; poverty

Confluence versus Ample Sets in Probabilistic Branching Time

To improve the efficiency of model checking in general, and probabilistic model checking in particular, several reduction techniques have been introduced. Two of these, confluence reduction and partial-order reduction by means of ample sets, are based on similar principles, and both preserve branching-time properties for probabilistic models. Confluence reduction has been introduced for probabilistic automata, whereas ample set reduction has been introduced for Markov decision processes. In this presentation we will explore the relationship between confluence and ample sets. To this end, we redefine confluence reduction to handle MDPs. We show that all non-trivial ample sets consist of confluent transitions, but that the converse is not true. We also show that the two notions coincide if the definition of confluence is restricted, and point out the relevant parts where the two theories differ. The results we present also hold for non-probabilistic models, as our theorems can just as well be applied in a context where all transitions are non-probabilistic. To show a practical application of our results, we adapt a state space generation technique based on representative states, already known in combination with confluence reduction, so that it can also be applied with partial-order reduction

Food Security and Economic Growth: An Asian Perspective

Food security is an elusive concept. Many economists doubt that it has any precise meaning at all. Having enough to eat on a regular basis, however, is a powerful human need, and satisfying this need drives household behavior in both private and public markets in predictable ways. Indeed, the historical record suggests that policy initiatives by central governments to satisfy this need for food security—at the level of both households and national markets—can speed economic growth in countries where a substantial proportion of the population does not get enough to eat. Paradoxically, in most successfully developing countries, especially those in the rice-based economies of Asia, the public provision of food security quickly slips from its essential role as an economic stimulus into a political response to the pressures of rapid structural transformation, thereby becoming a drag on economic efficiency. The long-run relationship between food security and economic growth thus tends to switch from positive to negative over the course of development. Because of inevitable inertia in the design and implementation of public policy, this switch presents a serious challenge to the design of an appropriate food policy.Food security, democracy, foreign assistance, economic development