to software development, with perhaps the most prominent being object-orientation (00). In addition, the focus on process im-provement has increased the demand for software measures, or metrics with which to manage the process. The need for such metrics is particularly acute when an organization is adopting a

is concerned with the last of these. The basic principle is easily stated.' A commodity should be produced if the costs can be covered by the sum of revenues and a properly defined measure of consumer's surplus. The optimum amount is then found by equating the demand price and the marginal cost

and rotational velocity is chosen by maximizing an objective function. The objective function includes a measure of progress towards a goal location, the forward velocity of the robot, and the distance to the next obstacle on the trajectory. In extensive experiments the approach presented here has been found

This paper considers optimal testing of model comparison hypotheses for misspeci…ed unconditional moment restriction models. We adopt the generalized Neyman-Pearson optimality criterion, which focuses on the convergence rates of the type I and II error probabilities under …xed global alternatives, and derive an optimal but practically infeasible test. We then propose feasible approximation test statistics to the optimal one. For linear instrumental variable regression models, the conventional empirical likelihood ratio test statistic emerges. For general nonlinear moment restrictions, we propose a new test statistic based on an iterative algorithm. We derive the asymptotic properties of these test statistics. JEL classi…cation: C12; C14; C52

that participate. These elementary signals typically model coherent structures in the input signals, and they are chosen from a large, linearly dependent collection. The first part of this paper proposes a greedy pursuit algorithm, called Simultaneous Orthogonal Matching Pursuit, for simultaneous sparse

This paper investigates the application of the mutual infor“ criterion to evaluate a set of candidate features and to select an informative subset to be used as input data for a neural network classifier. Because the mutual information measures arbitrary dependencies between random variables

productivity, and output, I determine the implied path of prices predicted by the model. Because prices are not a stationary series, I present my results in terms of the predicted path of the price/unit labor cost ratio, where the parameters characterizing such paths are chosen to maximize the fit

desire loses some of its appeal. Direct reports of subjective well-being may have a useful role in the measurement of consumer preferences and social welfare, if they can be done in a credible way. Indeed, economists have already made much use of subjective well-being data. From 2001 to 2005, more than

Kernel based methods are increasingly being used for data modeling because of their conceptual simplicity and outstanding performance on many tasks. However, the kernel function is often chosen using trial-and-error heuristics. In this paper we address the problem of measuring the degree

. The superposition is approximated by a correlated Markov modulated Poisson process (MMPP), which is chosen such that several of its statistical characteristics identically match those of the superposition. Matrix analytic methods are then used to evaluate system performance measures. In particular, we obtain