An Acceptance-Rejection Algorithm for the Kolmogorov Distribution

We discuss an acceptance-rejection algorithm for the random number generation from the Kolmogorov distribution. Since the cumulative distribution function (CDF) is a functions series and we need the density distribution function in our algorithm, we prove that the series of the derivatives converges uniformly in order to can derive term by term the functions series; also we provide a similar proof for showing that the ratio between the target Kolmogorov density and the auxiliary density implemented is bounded. Finally, for the application in the algorithm we propose to approximate the density of Kolmogorov distribution by truncation series where the truncation is posed as far away as possible according to the precision of the calculator, we asses the accuracy of this method by a simulation study

An extension of the Unified Skew-Normal family of distributions and application to Bayesian binary regression

We consider the general problem of Bayesian binary regression with a large number of covariates. We introduce a new class of distributions, the Perturbed Unified Skew Normal (PSUN), which generalizes the SUN class and we show that the new class is conjugate to any binary regression model, provided that the link function may be expressed as a scale mixture of Gaussian densities. We discuss in detail the probit and logistic cases. The proposed methodology, based on a straightforward Gibbs sampler algorithm, can be always applied. In particular, in the p > n case, it shows better performances both in terms of mixing and accuracy, compared to the existing methods

Successful retrograde recanalization of internal jugular vein passing from omolateral external jugular vein

Severe stenosis and/or thrombosis of the internal jugular vein could be managed through a novel technique herein reported. Recanalization can be achieved passing through the omolateral external jugular vein

Parietal resting-state EEG alpha source connectivity is associated with subcortical white matter lesions in HIV-positive people

Objective Parietal resting-state electroencephalographic (rsEEG) alpha (8–10 Hz) source connectivity is abnormal in HIV-positive persons. Here we tested whether this abnormality may be associated with subcortical white matter vascular lesions in the cerebral hemispheres. Methods Clinical, rsEEG, and magnetic resonance imaging (MRI) datasets in 38 HIV-positive persons and clinical and rsEEG datasets in 13 healthy controls were analyzed. Radiologists visually evaluated the subcortical white matter hyperintensities from T2-weighted FLAIR MRIs (i.e., Fazekas scale). In parallel, neurophysiologists estimated the eLORETA rsEEG source lagged linear connectivity from parietal cortical regions of interest. Results Compared to the HIV participants with no/negligible subcortical white matter hyperintensities, the HIV participants with mild/moderate subcortical white matter hyperintensities showed lower parietal interhemispheric rsEEG alpha lagged linear connectivity. This effect was also observed in HIV-positive persons with unimpaired cognition. This rsEEG marker allowed good discrimination (area under the receiver operating characteristic curve > 0.80) between the HIV-positive individuals with different amounts of subcortical white matter hyperintensities. Conclusions The parietal rsEEG alpha source connectivity is associated with subcortical white matter vascular lesions in HIV-positive persons, even without neurocognitive disorders. Significance Those MRI-rsEEG markers may be used to screen HIV-positive persons at risk of neurocognitive disorders

The AGILE Mission

AGILE is an Italian Space Agency mission dedicated to observing the gamma-ray Universe. The AGILE's very innovative instrumentation for the first time combines a gamma-ray imager (sensitive in the energy range 30 MeV-50 GeV), a hard X-ray imager (sensitive in the range 18-60 keV), a calorimeter (sensitive in the range 350 keV-100 MeV), and an anticoincidence system. AGILE was successfully launched on 2007 April 23 from the Indian base of Sriharikota and was inserted in an equatorial orbit with very low particle background. Aims. AGILE provides crucial data for the study of active galactic nuclei, gamma-ray bursts, pulsars, unidentified gamma-ray sources, galactic compact objects, supernova remnants, TeV sources, and fundamental physics by microsecond timing. Methods. An optimal sky angular positioning (reaching 0.1 degrees in gamma- rays and 1-2 arcmin in hard X-rays) and very large fields of view (2.5 sr and 1 sr, respectively) are obtained by the use of Silicon detectors integrated in a very compact instrument. Results. AGILE surveyed the gamma- ray sky and detected many Galactic and extragalactic sources during the first months of observations. Particular emphasis is given to multifrequency observation programs of extragalactic and galactic objects. Conclusions. AGILE is a successful high-energy gamma-ray mission that reached its nominal scientific performance. The AGILE Cycle-1 pointing program started on 2007 December 1, and is open to the international community through a Guest Observer Program

Copule condizionate: applicazione nel calcolo del value-at-risk

We suggest a method with a view to compute the Value-at-Risk of a portfolio composed by two stock indices. In order to model the dependence between the two indices we use a conditional copula model, in particular we assume Archimedean copula and the parameter of the copula is function of another variable, that is a volatility index in this work. We use a non-parametric approach in order to estimate the function. With a view to model the individual indices we use an AR(1) process in order to compute the conditional means and a GARCH(1,1) process in order to compute the conditional variances. Finally the Value-at-Risk estimates are checked through the test of Kupiec and the test of Christoffersen and the estimates that passes the verification are compared through the AIC

Three-dimensional tuning profile of motor cortical activity during arm movements

The neural firing activity in the primary motor cortex was modulated to the direction of hand movement. In contradiction to previous reports, a recent study found a non-uniform distribution of preferred directions of neurons while monkeys made center-out reaching movements in a horizontal plane. To re-examine the distribution of preferred directions in three-dimensional space, we recorded the activity of 117 arm-related neurons in the primary motor cortex and electromyographic signals of shoulder and upper arm muscles of a monkey while it performed center-out reaching movements towards 26 target points placed on a sphere-shaped workspace. We found that the distribution of preferred directions of neurons was non-uniform and that it was correlated to muscle activity and arm joint rotations

Bayesian Hierarchical Copula Models with a Dirichlet–Laplace Prior

We discuss a Bayesian hierarchical copula model for clusters of financial time series. A similar approach has been developed in recent paper. However, the prior distributions proposed there do not always provide a proper posterior. In order to circumvent the problem, we adopt a proper global–local shrinkage prior, which is also able to account for potential dependence structures among different clusters. The performance of the proposed model is presented via simulations and a real data analysis

Bayesian Hierarchical Copula Models with a Dirichlet–Laplace Prior

We discuss a Bayesian hierarchical copula model for clusters of financial time series. A similar approach has been developed in recent paper. However, the prior distributions proposed there do not always provide a proper posterior. In order to circumvent the problem, we adopt a proper global–local shrinkage prior, which is also able to account for potential dependence structures among different clusters. The performance of the proposed model is presented via simulations and a real data analysis