A one-way randomeffectsmodel is consideredfor the log-transformedshift-longpersonal exposure measurements, where the random effect in the model represents an effect due to the worker. Following a previousapproach,we address a hypothesis-testingproblem involving the proportionof workers for whom the mean exposure exceeds the occupational exposure limit. A conŽ dence interval is constructed for t...

In this paper, I study the e¤ects of overcon…dence on incentive contracts in a moral-hazard framework in which principal and agent knowingly hold asymmetric beliefs regarding the probability of success of their enterprise. Agent overcon…dence can have con‡icting e¤ects on the equilibrium contract. On the one hand, an overcon…dent agent disproportionately values successcontingent payments, and t...

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 robust, task independent spoken Language Identi cation (LID) system which uses a Large Vocabulary Continuous Speech Recognition (LVCSR) module for each language to choose the most likely language spoken is described. The acoustic analysis uses mean cepstral removal on mel scale cepstral coe cients to compensate for di erent input channels. The system has been trained on 5 languages: English, ...

The hidden Markov model (HMM) is one type of stochastic signal model which is widely used in modeling and classi cation problems. Yet the more advanced statistical inference in this model has been omitted almost in all applications. In this paper we show how to calculate in practise the likelihood based con dence intervals for model parameters and further for the probability of a new case to be...

In this article, we obtain an importance resampling formula to reduce the amount of resampling necessary for the construction of bootstrap con dence regions. In the one-dimensional case, the formula reduces to that of Jones (1988) and Do & Hall (1991). However, the methods employed by previous authors are not tamed for direct generalization to multi-dimensional parameters. Therefore no formula ...

This paper describes a newly developed statistical approach for modelling positional error of geometric features in GIS. The generic statistical models for N-dimensional features are ® rstly derived. The models for oneand twodimensional features are then developed as the speci® c cases of the generic models. In each dimension, the GIS features are classi® ed as points, line segments and line fe...

The general properties of two commonly used methods of interval estimation for population parameters in physics are examined Both of these methods em ploy the likelihood function i Obtaining an interval by nding the points where the likelihood decreases from its maximum by some speci ed ratio ii Obtaining an interval by nding points corresponding to some speci ed fraction of the total integral ...