abstract background and aim: the intolerance of uncertainty model was initially developed as an explanation for worry within the context of generalized anxiety disorder. however, recent research has identified intolerance of uncertainty (iu) as a transdiagnostic maintaining factor across the anxiety disorders. the aim of the present study was to compare the intolerance of uncertainty in patient...

The authors argue that alternatives to the traditional numeric methods of measuring people's uncertainty may prove to hold important advantages under some conditions. In 3 experiments, the authors compared verbal measures involving responses such as very likely, and numeric measures involving responses such as 80% chance. The verbal measures were found to show more sensitivity to various manipu...

The paper discusses the problem of modelling linguistic uncertainty, which is the uncertainty produced by statements in natural language. For example, the vague statement`Mary is young' produces uncertainty about Mary's age. We concentrate on simple aarmative statements of the typèsubject is predicate', where the predicate satisses a special condition called monotonicity. For this case, we mode...

In this paper, we propose a methodology for constructing uncertainty sets within the framework of robust optimization for linear optimization problems with uncertain parameters. Our approach relies on decision-maker risk preferences. Specifically, we utilize the theory of coherent risk measures initiated by Artzner et al. [3], and show that such risk measures, in conjunction with the support of...

Uncertainty importance measures typically reflect the degree to which uncertainty about risk and reliability parameters at the component level influences uncertainty about parameters at the system level. The definition of these measures is typically founded on a Bayesian perspective where subjective probabilities are used to express epistemic uncertainty; hence, they do not reflect the effect o...

The paper discusses the problem of modelling linguistic uncertainty, which is the uncertainty produced by statements in natural language. For example, the vague statement`Mary is young' produces uncertainty about Mary's age. We concentrate on simple aarmative statements of the typèsubject is predicate', where the predicate satisses a special condition called monotonicity. For this case, we mode...

Position uncertainty (delocalization) measures for a particle on the sphere are proposed and illustrated on several examples of states. The new measures are constructed using suitably the standard multiplication angle operator variances. They are shown to depend solely on the state of the particle and to obey uncertainty relations of the Schrödinger–Robertson type. A set of Hermitian operators ...

This work studies the use of observation uncertainty measures for improving the speech recognition performance of an exemplar-based source separation based front end. To generate the observation uncertainty estimates for the enhanced features, we propose the use of heuristic methods based on the sparse representation of the noisy signal in the exemplar-based source separation algorithm. The eff...

We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee’s Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-hor...

Here H(X) measures the average uncertainty associated with the random variable X. If X is the lifetime of a system and if the system has survived up to time t, then to measure the uncertainty about the remaining lifetime of such a system the measure (1) is not appropriate. Ebrahimi (1996) proposed a measure which measures the uncertainty about the remaining lifetime of a system if it is working...