Instituto Tecnológico Autónomo de México

About: Instituto Tecnológico Autónomo de México is a education organization based out in Mexico City, Mexico. It is known for research contribution in the topics: Politics & Population. The organization has 1098 authors who have published 2532 publications receiving 39083 citations. The organization is also known as: Instituto Tecnologico Autonomo de Mexico & Mexico Autonomous Institute of Technology.

Using the bootstrap for statistical inference on random graphs

Abstract: In this paper we propose a new nonparametric approach to network inference that may be viewed as a fusion of block sampling procedures for temporally and spatially dependent processes with the classical network methodology. We develop estimation and uncertainty quantification procedures for network mean degree using a “patchwork” sample and nonparametric bootstrap, under the assumption of unknown degree distribution. We provide a heuristic justification of asymptotic properties of the proposed “patchwork” sampling and present cross-validation methodology for selecting an optimal “patch” size. We validate the new “patchwork” bootstrap on simulated networks with short- and long-tailed mean degree distributions, and revisit the Erdos collaboration data to illustrate the proposed methodology. The Canadian Journal of Statistics xx: 1–22; 2015 © 2015 Statistical Society of Canada Resume Les auteurs proposent une approche non parametrique pour l'inference dans les reseaux qui peut etre decrite comme une fusion entre la methodologie classique pour les reseaux et des procedures d’echantillonnage par bloc pour des processus presentant une dependance spatiale et temporelle. Ils developpent des procedures permettant d'estimer le degre moyen du reseau et d'en mesurer l'incertitude grâce a l’echantillonnage en mosai que et au bootstrap non parametrique, sous l'hypothese que la distribution du degre est inconnue. Les auteurs presentent une justification heuristique des proprietes asymptotiques de l’echantillonnage en mosai que propose et decrivent une methodologie de validation croisee afin de choisir la taille optimale des pieces de la mosai que. Ils valident le bootstrap pour la mosai que en simulant des reseaux dont la distribution du degre moyen presente des queues lourdes ou legeres. Ils illustrent egalement leur methodologie a l'aide des donnees de collaboration d'Erdos. La revue canadienne de statistique xx: 1–22; 2015 © 2015 Societe statistique du Canada

Gaussian kinetic model for granular gases.

Abstract: A kinetic model for the Boltzmann equation is proposed and explored as a practical means to investigate the properties of a dilute granular gas. It is shown that all spatially homogeneous initial distributions approach a universal ”homogeneous cooling solution” after a few collisions. The homogeneous cooling solution (HCS) is studied in some detail and the exact solution is compared with known results for the hard sphere Boltzmann equation. It is shown that all qualitative features of the HCS, including the nature of over population at large velocities, are reproduced semi-quantitatively by the kinetic model. It is also shown that all the transport coefficients are in excellent agreement with those from the Boltzmann equation. Also, the model is specialized to one having a velocity independent collision frequency and the resulting HCS and transport coefficients are compared to known results for the Maxwell Model. The potential of the model for the study of more complex spatially inhomogeneous states is discussed.

Sector specific impacts of macroeconomic fundamentals on the Swiss stock market

Abstract: A large body of evidence indicates that macroeconomic and financial variables are dynamically interrelated. In an international setup, we analyze the impacts of macroeconomic shocks on various sector indices of the Swiss stock market. We use a VECM model to disentangle local and foreign as well as macroeconomic andfinancial effects. Sector subindexes diverge to an important extent in their sensitivity to news about fundamental variables, a fact to be taken into account for asset allocation. JEL codes: E44, G15