Graphic methods for displaying uncertainty are often the most concise and informative way to communicate abstract concepts. Presentation methods currently in use for the display and interpretation of scientific uncertainty are reviewed. Numerous subjective and objective uncertainty display methods are presented, including qualitative assessments, node and arrow diagrams, standard statistical me...

A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are the beta-normal (Eugene et al. (2002)); beta-Gumbel (Nadarajah and Kotz (2004)); beta-exponential (Nadarajah and Kotz (2006)); beta-Weibull (Famoye et al. (2005)); beta-Rayleigh (Akinsete and Lowe (2008)); beta-Laplace (Kozubowski and Nadarajah (2008)); and beta-Par...

In this paper, we investigate some statistical properties of multiplication mod 2 for cryptographic use. For this purpose, we introduce a family of T-functions similar to modular multiplication, which we call M-functions. We obtain the probability distribution of M-functions as vectorial Boolean functions. At first, we determine the joint probability distribution of arbitrary number of the outp...

This paper presents a model based approach to human body tracking in which the 2D silhouette of a moving human and the corresponding 3D skeletal structure are encapsulated within a non-linear Point Distribution Model. This statistical model allows a direct mapping to be achieved between the external boundary of a human and the anatomical position. It is shown how this information, along with th...

We discuss a family of time-reversible, scale-invariant diffusions with singular coefficients. In analogy with the standard Gaussian theory, a corresponding family of generalized characteristic functions provides a useful tool for proving limit theorems resulting in non-Gaussian, scale-invariant diffusions. We apply the generalized characteristic functions in combination with a martingale const...

We describe a Bayesian approach to estimating luminosity functions. We derive the likelihood function and posterior probability distribution for the luminosity function, given the observed data, and we compare the Bayesian approach with maximum-likelihood by simulating sources from a Schechter function. For our simulations confidence intervals derived from bootstrapping the maximum-likelihood e...

How to test the effect of density estimation methods is the key problem in the statistics. This paper presents a new criterion for assessing the effect of density estimation to select the suitable density estimation method, using the maximum-entropy non-Gaussian measurement. Comparing withχ2-test and Dn-test, the method avoids the problem of the data interval division, and it is suitable for an...

To develop 8 reliable computer vision system, the employed algorithm must guarantee good output quality. In this Study. to ensure t h 0 quality of the pose estimated from line features. two simple teet functions based on Statistical hypothesis testing are defined. First, an error function based on the relation between the line features and Some quality thresholds is defined. By using the first ...