Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Upper-mantle seismic anisotropy from SKS splitting in the South American stable platform: A test of asthenospheric flow models beneath the lithosphere

Upper-mantle seismic anisotropy has been extensively used to infer both present and past deformation processes at lithospheric and asthenospheric depths. Analysis of shear-wave splitting (mainly from core-refracted SKS phases) provides information regarding upper-mantle anisotropy. We present average measurements of fast-polarization directions at 21 new sites in poorly sampled regions of intra-plate South America, such as northern and northeastern Brazil. Despite sparse data coverage for the South American stable platform, consistent orientations are observed over hundreds of kilometers. Over most of the continent, the fast-polarization direction tends to be close to the absolute plate motion direction given by the hotspot reference model HS3-NUVEL-1A. A previous global comparison of the SKS fast-polarization directions with flow models of the upper mantle showed relatively poor correlation on the continents, which was interpreted as evidence for a large contribution of ""frozen"" anisotropy in the lithosphere. For the South American plate, our data indicate that one of the reasons for the poor correlation may have been the relatively coarse model of lithospheric thicknesses. We suggest that improved models of upper-mantle flow that are based on more detailed lithospheric thicknesses in South America may help to explain most of the observed anisotropy patterns.

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

Beyond the average: Detecting global singular nodes from local features in complex networks

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barabasi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks. Copyright (C) EPLA, 2009