Exact Bayesian curve fitting and signal segmentation.

We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem

Developing a conceptual framework for an evaluation system for the NIAID HIV/AIDS clinical trials networks

Globally, health research organizations are called upon to re-examine their policies and practices to more efficiently and effectively address current scientific and social needs, as well as increasing public demands for accountability

Evaluation of large research initiatives: outcomes, challenges, and methodological considerations

The authors synthesize relevant literature and findings of evaluations of four large-scale, federally funded scientific research programs in the United States to identify desired outcomes of these types of programs, major evaluation chal-lenges, and methodological principles and approaches. Evaluators face numer-ous contextual, political, and methodological challenges in evaluating big science. The authors propose that these may be addressed through participatory planning, such as concept mapping, triangulation of evidence, use of promising methodologies, and a systems approac