Singular random matrix decompositions: distributions.

Assuming that Y has a singular matrix variate elliptically contoured distribution with respect to the Hausdorff measure, the distributions of several matrices associated to QR, modified QR, SV and Polar decompositions of matrix Y are determined, for central and non-central, non-singular and singular cases, as well as their relationship to the Wishart and Pseudo-Wishart generalized singular and non-singular distributions. We present a particular example for the Karhunen-Lòeve decomposition. Some of these results are also applied to two particular subfamilies of elliptical distributions, the singular matrix variate normal distribution and the singular matrix variate symmetric Pearson type VII distribution

SINGULAR RANDOM MATRIX DECOMPOSITIONS: DISTRIBUTIONS.

Assuming that Y has a singular matrix variate elliptically contoured distribution with respect to the Hausdorff measure, the distributions of several matrices associated to QR, modified QR, SV and Polar decompositions of matrix Y are determined, for central and non-central, non-singular and singular cases, as well as their relationship to the Wishart and Pseudo-Wishart generalized singular and non-singular distributions. We present a particular example for the Karhunen-Lòeve decomposition. Some of these results are also applied to two particular subfamilies of elliptical distributions, the singular matrix variate normal distribution and the singular matrix variate symmetric Pearson type VII distribution.

Nonparametric Estimation of Functional Dynamic Factor Model

For many phenomena, data are collected on a large scale, resulting in high-dimensional and high-frequency data. In this context, functional data analysis (FDA) is attracting interest. FDA deals with data that are defined on an intrinsically infinite-dimensional space. These data are called functional data. However, the infinite-dimensional data might be driven by a small number of latent variables. Hence, factor models are relevant for functional data. In this paper, we study functional factor models for time-dependent functional data. We propose nonparametric estimators under stationary and nonstationary processes. We obtain estimators that consider the time-dependence property. Specifically, we use the information contained on the covariances at different lags. We show that the proposed estimators are consistent. Through Monte Carlo simulations, we find that our methodology outperforms the common estimators based on functional principal components. We also apply our methodology to monthly yield curves. In general, the suitable integration of time-dependent information improves the estimation of the latent factors.Comment: 28 pages, 6 figure

Noncentral elliptical configuration density

AbstractThe noncentral configuration density, derived under an elliptical model, generalizes and corrects the Gaussian configuration and some Pearson results. Partition theory is then used to obtain explicit configuration densities associated with matrix variate symmetric Kotz type distributions (including the normal distribution), matrix variate Pearson type VII distributions (including t and Cauchy distributions), the matrix variate symmetric Bessel distribution (including the Laplace distribution) and the matrix variate symmetric Jensen-logistic distribution

Medios de comunicación y derecho a la información en Jalisco, 2016

Se rescata el acontecer mediático y las trasformaciones más relevantes en materia de derecho a la información entre 2015 y 2016. Este periodo arroja interesantes análisis con respecto a temas como los cambios del sistema de medios en Jalisco; la trasparencia y el acceso a la información, así como la configuración de quienes integran las instituciones que vigilan su aplicación; la transición a la televisión digital terrestre; los desaparecidos y la falta de acceso a la información, y el rostro de la prensa local a partir de sus capacidades financieras desde la perspectiva de su independencia editorial. Asimismo, se registraron hechos importantes que están marcando un parteaguas en el estado, como la alerta de violencia contra las mujeres en Jalisco, la iniciativa ciudadana #Ley3de3, las modificaciones al Premio Jalisco de Periodismo y las implicaciones del nuevo sistema penal para los medios y los periodistas. Cierra con un espacio para mantener viva la memoria de los profesionales de la comunicación que han participado en la construcción del acontecer informativo, cultural y de entretenimiento local

Miradas desde la historia social y la historia intelectual: América Latina en sus culturas: de los procesos independistas a la globalización

Fil: Benito Moya, Silvano G. A. Universidad Católica de Córdoba. Facultad de Filosofía y Humanidades; Argentina.Fil: Universidad Católica de Córdoba. Facultad de Filosofía y Humanidades; Argentina

La renovación de la palabra en el bicentenario de la Argentina : los colores de la mirada lingüística

El libro reúne trabajos en los que se exponen resultados de investigaciones presentadas por investigadores de Argentina, Chile, Brasil, España, Italia y Alemania en el XII Congreso de la Sociedad Argentina de Lingüística (SAL), Bicentenario: la renovación de la palabra, realizado en Mendoza, Argentina, entre el 6 y el 9 de abril de 2010. Las temáticas abordadas en los 167 capítulos muestran las grandes líneas de investigación que se desarrollan fundamentalmente en nuestro país, pero también en los otros países mencionados arriba, y señalan además las áreas que recién se inician, con poca tradición en nuestro país y que deberían fomentarse. Los trabajos aquí publicados se enmarcan dentro de las siguientes disciplinas y/o campos de investigación: Fonología, Sintaxis, Semántica y Pragmática, Lingüística Cognitiva, Análisis del Discurso, Psicolingüística, Adquisición de la Lengua, Sociolingüística y Dialectología, Didáctica de la lengua, Lingüística Aplicada, Lingüística Computacional, Historia de la Lengua y la Lingüística, Lenguas Aborígenes, Filosofía del Lenguaje, Lexicología y Terminología

Transfer entropy as a variable selection methodology of cryptocurrencies in the framework of a high dimensional predictive model.

We determine the number of statistically significant factors in a high dimensional predictive model of cryptocurrencies using a random matrix test. The applied predictive model is of the reduced rank regression (RRR) type; in particular, we choose a flavor that can be regarded as canonical correlation analysis (CCA). A variable selection of hourly cryptocurrencies is performed using the Symbolic estimation of Transfer Entropy (STE) measure from information theory. In simulated studies, STE shows better performance compared to the Granger causality approach when considering a nonlinear system and a linear system with many drivers. In the application to cryptocurrencies, the directed graph associated to the variable selection shows a robust pattern of predictor and response clusters, where the community detection was contrasted with the modularity approach. Also, the centralities of the network discriminate between the two main types of cryptocurrencies, i.e., coins and tokens. On the factor determination of the predictive model, the result supports retaining more factors contrary to the usual visual inspection, with the additional advantage that the subjective element is avoided. In particular, it is observed that the dynamic behavior of the number of factors is moderately anticorrelated with the dynamics of the constructed composite index of predictor and response cryptocurrencies. This finding opens up new insights for anticipating possible declines in cryptocurrency prices on exchanges. Furthermore, our study suggests the existence of specific-predictor and specific-response factors, where only a small number of currencies are predominant

Singular random matrix decompositions: distributions

Assuming that Y has a singular matrix variate elliptically contoured distribution with respect to the Hausdorff measure, the distributions of several matrices associated to QR, modified QR, SV and polar decompositions of matrix Y are determined, for central and non-central, non-singular and singular cases, as well as their relationship to the Wishart and pseudo-Wishart generalized singular and non-singular distributions. Some of these results are also applied to two particular subfamilies of elliptical distributions, the singular matrix variate normal distribution and the singular matrix variate symmetric Pearson type VII distribution.Non-central singular distribution Generalized Wishart and pseudo-Wishart distributions Elliptical distribution SVD QR Modified QR and polar decompositions

Nonparametric estimation of functional dynamic factor model

Data can be assumed to be continuous functions defined on an infinite-dimensional space for many phenomena. However, the infinite-dimensional data might be driven by a small number of latent variables. Hence, factor models are relevant for functional data. In this paper, we study functional factor models for time-dependent functional data. We propose nonparametric estimators under stationary and nonstationary processes. We obtain estimators that consider the time-dependence property. Specifically, we use the information contained in the covariances at different lags. We show that the proposed estimators are consistent. Through Monte Carlo simulations, we find that our methodology outperforms estimators based on functional principal components. We also apply our methodology to monthly yield curves. In general, the suitable integration of time-dependent information improves the estimation of the latent factors