Bayesian Semiparametric Hierarchical Empirical Likelihood Spatial Models

We introduce a general hierarchical Bayesian framework that incorporates a flexible nonparametric data model specification through the use of empirical likelihood methodology, which we term semiparametric hierarchical empirical likelihood (SHEL) models. Although general dependence structures can be readily accommodated, we focus on spatial modeling, a relatively underdeveloped area in the empirical likelihood literature. Importantly, the models we develop naturally accommodate spatial association on irregular lattices and irregularly spaced point-referenced data. We illustrate our proposed framework by means of a simulation study and through three real data examples. First, we develop a spatial Fay-Herriot model in the SHEL framework and apply it to the problem of small area estimation in the American Community Survey. Next, we illustrate the SHEL model in the context of areal data (on an irregular lattice) through the North Carolina sudden infant death syndrome (SIDS) dataset. Finally, we analyze a point-referenced dataset from the North American Breeding Bird survey that considers dove counts for the state of Missouri. In all cases, we demonstrate superior performance of our model, in terms of mean squared prediction error, over standard parametric analyses.Comment: 29 pages, 3 figue

Eigenvector-Based Centrality Measures for Temporal Networks

Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centrality. We consider a temporal network with N nodes as a sequence of T layers that describe the network during different time windows, and we couple centrality matrices for the layers into a supra-centrality matrix of size NTxNT whose dominant eigenvector gives the centrality of each node i at each time t. We refer to this eigenvector and its components as a joint centrality, as it reflects the importances of both the node i and the time layer t. We also introduce the concepts of marginal and conditional centralities, which facilitate the study of centrality trajectories over time. We find that the strength of coupling between layers is important for determining multiscale properties of centrality, such as localization phenomena and the time scale of centrality changes. In the strong-coupling regime, we derive expressions for time-averaged centralities, which are given by the zeroth-order terms of a singular perturbation expansion. We also study first-order terms to obtain first-order-mover scores, which concisely describe the magnitude of nodes' centrality changes over time. As examples, we apply our method to three empirical temporal networks: the United States Ph.D. exchange in mathematics, costarring relationships among top-billed actors during the Golden Age of Hollywood, and citations of decisions from the United States Supreme Court.Comment: 38 pages, 7 figures, and 5 table

Estimating the reproductive number, total outbreak size, and reporting rates for Zika epidemics in South and Central America

As South and Central American countries prepare for increased birth defects from Zika virus outbreaks and plan for mitigation strategies to minimize ongoing and future outbreaks, understanding important characteristics of Zika outbreaks and how they vary across regions is a challenging and important problem. We developed a mathematical model for the 2015 Zika virus outbreak dynamics in Colombia, El Salvador, and Suriname. We fit the model to publicly available data provided by the Pan American Health Organization, using Approximate Bayesian Computation to estimate parameter distributions and provide uncertainty quantification. An important model input is the at-risk susceptible population, which can vary with a number of factors including climate, elevation, population density, and socio-economic status. We informed this initial condition using the highest historically reported dengue incidence modified by the probable dengue reporting rates in the chosen countries. The model indicated that a country-level analysis was not appropriate for Colombia. We then estimated the basic reproduction number, or the expected number of new human infections arising from a single infected human, to range between 4 and 6 for El Salvador and Suriname with a median of 4.3 and 5.3, respectively. We estimated the reporting rate to be around 16% in El Salvador and 18% in Suriname with estimated total outbreak sizes of 73,395 and 21,647 people, respectively. The uncertainty in parameter estimates highlights a need for research and data collection that will better constrain parameter ranges.Comment: 35 pages, 16 figure

Modeling Range Dynamics In Heterogeneous Landscapes: Invasion Of The Hemlock Woolly Adelgid In Eastern North America

Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951–2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.Organismic and Evolutionary Biolog

Multiabsorber Transition-Edge Sensors for X-Ray Astronomy

We are developing arrays of position-sensitive microcalorimeters for future x-ray astronomy applications. These position-sensitive devices commonly referred to as hydras consist of multiple x-ray absorbers, each with a different thermal coupling to a single-transition-edge sensor microcalorimeter. Their development is motivated by a desire to achieve very large pixel arrays with some modest compromise in performance. We report on the design, optimization, and first results from devices with small pitch pixels (<75 m) being developed for a high-angular and energy resolution imaging spectrometer for Lynx. The Lynx x-ray space telescope is a flagship mission concept under study for the National Academy of Science 2020 decadal survey. Broadband full-width-half-maximum (FWHM) resolution measurements on a 9-pixel hydra have demonstrated E(FWHM) = 2.23 0.14 eV at Al-K, E(FWHM) = 2.44 0.29 eV at Mn-K, and E(FWHM) = 3.39 0.23 eV at Cu-K. Position discrimination is demonstrated to energies below <1 keV and the device performance is well-described by a finite-element model. Results from a prototype 20-pixel hydra with absorbers on a 50-m pitch have shown E(FWHM) = 3.38 0.20 eV at Cr-K1. We are now optimizing designs specifically for Lynx and extending the number of absorbers up to 25/hydra. Numerical simulation suggests optimized designs could achieve 3 eV while being compatible with the bandwidth requirements of the state-of-the art multiplexed readout schemes, thus making a 100,000 pixel microcalorimeter instrument a realistic goal

Competitive Boosterism: How Milwaukee Lost the Braves

By any measure, major-league baseball in North America surely qualifies as big business. The national pastime is a vital component of today\u27s urban political economy, and baseball teams resemble other high-prestige businesses in that cities must compete for the privilege of hosting them - whatever their true worth. A study analyzes the transfer of the Milwaukee Braves baseball franchise to Atlanta in 1965 as the outcome of competitive boosterism or the active participation of local elites in luring trade, industry, and investment from other cities for the purpose of economic development

Prospectus, February 21, 2007

https://spark.parkland.edu/prospectus_2007/1005/thumbnail.jp