Gene expression data are influenced by multiple biological and technological factors leading to a wide range of dispersion scenarios, although skewed patterns are not commonly addressed in microarray analyses. In this study, the distribution pattern of several human transcriptomes has been studied on free-access microarray gene expression data. Our results showed that, even in previously normal...

We present experimental results from a broad investigation of intrinsic preferences for information. We examine whether people prefer negatively skewed or positively skewed information structures when they are equally informative, whether people prefer more or less informative information structures, and how individual preferences over the skewness and the degree of information relate to one an...

Recommender systems have been a hot research area recently. One of the most widely used methods is Collaborative Filtering(CF), which selects items for an individual user from other similar users. However, CF may not fully reflect the procedure of how people choose an item in real life, for users are more likely to ask friends for opinions instead of asking strangers with similar interests. Rec...

We study the skewness premium (SK) introduced by Bates (1991) in a general context using Lévy Processes. Under a symmetry condition Fajardo and Mordecki (2006) obtain that SK is given by the Bate’s x% rule. In this paper we study SK under the absence of that symmetry condition. More exactly, we derive sufficient conditions for SK to be positive, in terms of the characteristic triplet of the Lév...

We propose a simulation algorithm to estimate means, variances, and covariances for a set of order statistics from inverse-Gaussian (IG) distributions. Given a set of Monte Carlo data, the algorithm estimates these values simultaneously. Two types of control variates are used: internal uniform and external exponential. Simulation results show that exponential control variates work better, best ...

The densest amorphous packing of rigid particles is known as random close packing. It has long been appreciated that higher densities are achieved by using collections of particles with a variety of sizes. For spheres, the variety of sizes is often quantified by the polydispersity of the particle size distribution: the standard deviation of the radius divided by the mean radius. Several prior s...

Nonnormality of univariate data has been extensively examined previously (Blanca et al., Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(2), 78-84, 2013; Miceeri, Psychological Bulletin, 105(1), 156, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and edu...

We propose a formalism for estimating the skewness and angular power spectrum of a general Cosmic Microwave Background data set. We use the Edgeworth Expansion to define a non-Gaussian likelihood function that takes into account the anisotropic nature of the noise and the incompleteness of the sky coverage. The formalism is then applied to estimate the skewness of the publicly available 4 year ...

We introduce a skewness-based approach to measure tax progression and demand for redistribution. We provide a political economy foundation for a novel measure of skewness by expressing key properties of the classical model of voting over income redistribution (Meltzer and Richard, 1981) and the Prospect Of Upward Mobility (POUM) mechanism (Bènabou and Ok, 2001), as well as the conventional noti...

Independent component analysis (ICA) is an important unsupervised learning method. Most popular ICAmethods use kurtosis as a metric of non-Gaussianity to maximize, such as FastICA and JADE. However, their assumption of kurtosic sources may not always be satisfied in practice. For weak-kurtosic but skewed sources, kurtosis-based methods could fail while skewness-based methods seem more promising...