Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes

Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although the maximum composite likelihood estimator has frequentist properties akin to those of the usual maximum likelihood estimator, Bayesian inference based on composite likelihoods has yet to be explored. In this paper we investigate the use of the Metropolis--Hastings algorithm to compute a pseudo-posterior distribution based on the composite likelihood. Two methodologies for adjusting the algorithm are presented and their performance on approximating the true posterior distribution is investigated using simulated data sets and real data on spatial extremes of rainfall

Downscaling extremes: A comparison of extreme value distributions in point-source and gridded precipitation data

There is substantial empirical and climatological evidence that precipitation extremes have become more extreme during the twentieth century, and that this trend is likely to continue as global warming becomes more intense. However, understanding these issues is limited by a fundamental issue of spatial scaling: most evidence of past trends comes from rain gauge data, whereas trends into the future are produced by climate models, which rely on gridded aggregates. To study this further, we fit the Generalized Extreme Value (GEV) distribution to the right tail of the distribution of both rain gauge and gridded events. The results of this modeling exercise confirm that return values computed from rain gauge data are typically higher than those computed from gridded data; however, the size of the difference is somewhat surprising, with the rain gauge data exhibiting return values sometimes two or three times that of the gridded data. The main contribution of this paper is the development of a family of regression relationships between the two sets of return values that also take spatial variations into account. Based on these results, we now believe it is possible to project future changes in precipitation extremes at the point-location level based on results from climate models.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS287 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Markov-switching model for heat waves

Heat waves merit careful study because they inflict severe economic and societal damage. We use an intuitive, informal working definition of a heat wave-a persistent event in the tail of the temperature distribution-to motivate an interpretable latent state extreme value model. A latent variable with dependence in time indicates membership in the heat wave state. The strength of the temporal dependence of the latent variable controls the frequency and persistence of heat waves. Within each heat wave, temperatures are modeled using extreme value distributions, with extremal dependence across time accomplished through an extreme value Markov model. One important virtue of interpretability is that model parameters directly translate into quantities of interest for risk management, so that questions like whether heat waves are becoming longer, more severe or more frequent are easily answered by querying an appropriate fitted model. We demonstrate the latent state model on two recent, calamitous, examples: the European heat wave of 2003 and the Russian heat wave of 2010.Comment: Published at http://dx.doi.org/10.1214/15-AOAS873 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Black Power in a Lily-White School: The Black Campus Movement at Concordia College in Moorhead, Minnesota

Between the mid-1950s and through the 1970s, higher educational institutions throughout the United States underwent reforms in the name of what they termed “integration.” For the colleges and universities in the upper Midwest, these reforms included minority student recruitment and the creation of programs oriented towards diversity. Over time, a number of minority students began to act and react to the actions and attitudes of the various administrations, the campuses, and the community, resulting in a demonstration directly connected to the national phenomenon of “The Black Campus Movement,” (BCM) itself a submovement of the larger United States’ Black Power Movement of the mid-twentieth century. The historiography of the BCM has failed to examine more minor instances of the movement, instead focusing on larger institutions, violent demonstrations, or ones with a large proportion of black students compared to white students. This study expands that historiography by introducing a case-study on a BCM demonstration at Concordia College in Moorhead, Minnesota. Concordia was and still is a small, four-year liberal arts college with strong ties to Norwegian heritage and the Lutheran religion. In 1976, Concordia underwent a BCM demonstration when more than half of its very small black student population boycotted their classes and presented a list of demands to the administration. This study how and why this demonstration occurred, places Concordia within the larger historiography of the BCM, and provides a narrative account of how two cultures clashed at a small, predominantly white, Lutheran college in the upper Midwest

The effects of ozone and Fusarium root and crown rot on the growth and decline of alfalfa, Medicago sativa L.

Plant PathologyDoctor of Philosophy (Ph.D.

Donor KIR B Genotype Improves Progression-Free Survival of Non-Hodgkin Lymphoma Patients Receiving Unrelated Donor Transplantation

Donor killer immunoglobulin-like receptor (KIR) genotypes are associated with relapse protection and survival after allotransplantation for acute myelogenous leukemia. We examined the possibility of a similar effect in a cohort of 614 non-Hodgkin lymphoma (NHL) patients receiving unrelated donor (URD) T cell-replete marrow or peripheral blood grafts. Sixty-four percent (n = 396) of donor-recipient pairs were 10/10 allele HLA matched and 26% were 9/10 allele matched. Seventy percent of donors had KIR B/x genotype; the others had KIR A/A genotype. NHL patients receiving 10/10 HLA-matched URD grafts with KIR B/x donors experienced significantly lower relapse at 5 years (26%; 95% confidence interval [CI], 21% to 32% versus 37%; 95% CI, 27% to 46%; P = .05) compared with KIR A/A donors, resulting in improved 5-year progression-free survival (PFS) (35%; 95% CI, 26% to 44% versus 22%; 95% CI, 11% to 35%; P = .007). In multivariate analysis, use of KIR B/x donors was associated with significantly reduced relapse risk (relative risk [RR], .63, P = .02) and improved PFS (RR, .71, P = .008). The relapse protection afforded by KIR B/x donors was not observed in HLA-mismatched transplantations and was not specific to any particular KIR-B gene. Selecting 10/10 HLA-matched and KIR B/x donors should benefit patients with NHL receiving URD allogeneic transplantation

Partial Tail Correlation for Extremes

In order to understand structural relationships among sets of variables at extreme levels, we develop an extremes analogue to partial correlation. We begin by developing an inner product space constructed from transformed-linear combinations of independent regularly varying random variables. We define partial tail correlation via the projection theorem for the inner product space. We show that the partial tail correlation can be understood as the inner product of the prediction errors from transformed-linear prediction. We connect partial tail correlation to the inverse of the inner product matrix and show that a zero in this inverse implies a partial tail correlation of zero. We then show that under a modeling assumption that the random variables belong to a sensible subset of the inner product space, the matrix of inner products corresponds to the previously-studied tail pairwise dependence matrix. We develop a hypothesis test for partial tail correlation of zero. We demonstrate the performance in two applications: high nitrogen dioxide levels in Washington DC and extreme river discharges in the upper Danube basin