Constrained Maximum Likelihood (CML) is a new software module developed at Aptech Systems for the generation of maximum likelihood estimates of statistical models with general constraints on parameters. These constraints can be linear or nonlinear, equality or inequality. The software uses the Sequential Quadratic Programming method with various descent algorithms to iterate from a given starti...

The nominal orbit solution for an asteroid/comet resulting from a least squares t to astrometric observations is surrounded by a region containing solutions equally compatible with the data, the con dence region. If the observed arc is not too short, and for an epoch close to the observations, the con dence region in the 6-dimensional space of orbital elements is well approximated by an ellipso...

Constrained Maximum Likelihood (CML) is a new software module developed at Aptech Systems for the generation of maximum likelihood estimates of statistical models with general constraints on parameters. These constraints can be linear or nonlinear, equality or inequality. The software uses the Sequential Quadratic Programming method with various descent algorithms to iterate from a given starti...

This paper studies the causal e¤ect of individuals’overcon…dence and bounded rationality on asset markets. To do that, we combine a new market mechanism with an experimental design, where (1) players’interaction is centered on the inferences they make about each others’information, (2) overcon…dence in private information is controlled by the experimenter (i.e., used as a treatment), and (3) na...

An acoustic con dence measure for acceptance/rejection of recognition hypotheses for continuous speech utterances is proposed. This measure is useful for rejecting utterances that are out of domain, or contain out-of-vocabulary words or speech dis uencies. A phone-based approach is implemented so that a single global threshold can be applied to hypothesis rejection for any word sequence. Phone ...

Con dence intervals for the survival function and the cumulative hazard function are considered. These con dence intervals are based on an inversion of the likelihood ratio statistic. To do this two extensions of the likelihood, each of which yields meaningful likelihood ratio hypothesis tests and subsequent con dence intervals, are considered. The choice of the best extension is di cult. In th...

Multimodal fusion for identity veri cation has already shown great improvement compared to unimodal algorithms. In this paper, we propose to integrate con dence measures during the fusion process. We present a comparison of three di erent methods to generate such con dence information from unimodal identity veri cation systems. These methods can be used either to enhance the performance of a mu...

This paper proposes a probabilistic framework to de ne and evaluate con dence measures for word recognition. We describe a novel method to combine di erent knowledge sources and estimate the con dence in a word hypothesis, via a neural network. We also propose a measure of the joint performance of the recognition and con dence systems. The de nitions and algorithms are illustrated with results ...

—Experts are often not 100% con dent in their statements. In traditional fuzzy logic, the expert's degree of con dence in each of his or her statements is described by a number from the interval [0, 1]. However, due to similar uncertainty, an expert often cannot describe his or her degree by a single number. It is therefore reasonable to describe this degree by, e.g., a set of numbers. In this ...

The nominal orbit solution for an asteroid/comet resulting from a least squares t to astrometric observations is surrounded by a region containing solutions equally compatible with the data, the con dence region. If the observed arc is not too short, and for an epoch close to the observations, the con dence region in the 6-dimensional space of orbital elements is well approximated by an ellipso...