We give a novel method for performing statistically signi cant detection of speci ed object features which operates directly on X-ray (Gaussian) or radio-isotope (Poisson) tomographic projection data. The method is based on constructing an exact (1 )100% con dence region on the object derived by backprojecting a projection-domain con dence region into object space. The projection-domain con den...

In this paper, I devise a new way to construct con…dence sets for a parameter of interest in models comprised of a …nite number of moment inequalities. Many models of this form have appeared in the literature to date, particularly in the recent literature on partial identi…cation, but performing statistical inference in these settings is an area of ongoing research. Toward this end, I establish...

This paper compares di erent procedures to compute con dence intervals for parameters and quantiles of the Weibull, lognormal, and similar log-location-scale distributions from Type I censored data that typically arise from life test experiments. The procedures can be classi ed into three groups. The rst group contains procedures based on the commonlyused normal approximation for the distributi...

An unknown signal plus white noise is observed at n discrete time points. Within a large convex class of linear estimators of , we choose the estimator b that minimizes estimated quadratic risk. By construction, b is nonlinear. This estimation is done after orthogonal transformation of the data to a reasonable coordinate system. The procedure adaptively tapers the coeecients of the transformed ...

This paper presents a novel approach to using con dence scores for word graph rescoring. For each word in the system's vocabulary, we computed the probability that the observation is correct given its acoustic score. Afterwards, we used these probabilities for rescoring word graphs outputted by the recognizer. We will present some implementation details as well as accuracy improvements obtained...

The widespread use of networks makes information security a major concern where the underlying network (e.g., the Internet) is assumed to be insecure. Systems with security requirements typically must operate with a high degree of conndence { they must be highly assured. The task of designing and building secure systems raises a fundamental question, how do we know with conndence that our desig...

We investigate the assignment of error bars to future ow predictions based upon an optimized parameter set obtained from history matching. The error bars reeect measurement errors and uncertainty in the optimum parameter values obtained.

A growing empirical literature documents that social communication a ects individual trading behavior and market trading patterns in nancial markets. Motivated by this evidence, I develop an asset pricing model a la Kyle (1985) in which agents communicate information in social networks prior to trading. In particular, an agent who is more con dent in her private information puts greater weight ...

High-throughput experimental methods, such as yeast-two-hybrid and phage display, have fairly high levels of false positives (and false negatives). Thus the list of protein-protein interactions detected by such experiments would need additional wet laboratory validation. It would be useful if the list could be prioritized in some way. Advances in computational techniques for assessing the relia...

In this paper, a two-stage texture segmentation approach is proposed where an initial segmentation map is obtained through unsupervised clustering of MRSAR features and is followed by self-supervised or bootstrapped classi cation of wavelet features. The selfsupervised stage is based on a segmentation con dence map, where the regions of \high con dence" and \low con dence" are identi ed on the ...