University of California, Davis

About: University of California, Davis is a education organization based out in Davis, California, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 78770 authors who have published 180033 publications receiving 8064158 citations. The organization is also known as: UC Davis & UCD.

A Survey of z > 5.8 quasars in the Sloan Digital Sky Survey I: Discovery of three new quasars and the spatial density of luminous quasars at z ~ 6

Abstract: We present the results from a survey of i-dropout objects selected from ~1550 deg2 of multicolor imaging data from the Sloan Digital Sky Survey to search for luminous quasars at z 5.8. Objects with i*-z* > 2.2 and z* 0.90. The ARC 3.5 m spectrum of SDSSp J103027.10+052455.0 shows that over a range of ~300 A immediately blueward of the Lyα emission, the average transmitted flux is only 0.003 ± 0.020 times that of the continuum level, consistent with zero flux over a ~300 A range of the Lyα forest region and suggesting a tentative detection of the complete Gunn-Peterson trough. The existence of strong metal lines in the quasar spectra suggests early metal enrichment in the quasar environment. The three new objects, together with the previously published z = 5.8 quasar SDSSp J104433.04-012502.2, form a complete color-selected flux-limited sample at z 5.8. We estimate the selection function of this sample, taking into account the estimated variations in the quasar spectral energy distribution, as well as observational photometric errors. We find that at z = 6, the comoving density of luminous quasars at M1450 < -26.8 (H0 = 50 km s-1 Mpc-1, Ω = 1) is 1.1 × 10-9 Mpc-3. This is a factor of ~2 lower than that at z ~ 5 and is consistent with an extrapolation of the observed quasar evolution at z < 5. Using the current sample, we discuss the constraint on the shape of the quasar luminosity function and the implications for the contribution of quasars to the ionizing background at z ~ 6. The luminous quasars discussed in the paper have central black hole masses of several times 109 M⊙ by the Eddington argument, with likely dark halo masses on the order of 1013 M⊙. Their observed space density provides a sensitive test of models of quasar and galaxy formation at high redshift.

Robust Inference with Multi-Way Clustering

Abstract: In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM, that provcides cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g. Liang and Zeger (1986), Arellano (1987)) and relies on similar relatively weak distributional assumptions. Our method is easily implemented in statistical packages, such as Stata and SAS, that already offer cluster-robust standard errors when there is one-way clustering. The method is demonstrated by a Monte Carlo analysis for a two-way random effects model; a Monte Carlo analysis of a placebo law that extends the state-year effects example of Bertrand et al. (2004) to two dimensions; and by application to two studies in the empirical public/labor literature where two-way clustering is present.

Evolution and behavioural responses to human-induced rapid environmental change.

Abstract: Almost all organisms live in environments that have been altered, to some degree, by human activities. Because behaviour mediates interactions between an individual and its environment, the ability of organisms to behave appropriately under these new conditions is crucial for determining their immediate success or failure in these modified environments. While hundreds of species are suffering dramatically from these environmental changes, others, such as urbanized and pest species, are doing better than ever. Our goal is to provide insights into explaining such variation. We first summarize the responses of some species to novel situations, including novel risks and resources, habitat loss/fragmentation, pollutants and climate change. Using a sensory ecology approach, we present a mechanistic framework for predicting variation in behavioural responses to environmental change, drawing from models of decision-making processes and an understanding of the selective background against which they evolved. Where immediate behavioural responses are inadequate, learning or evolutionary adaptation may prove useful, although these mechanisms are also constrained by evolutionary history. Although predicting the responses of species to environmental change is difficult, we highlight the need for a better understanding of the role of evolutionary history in shaping individuals’ responses to their environment and provide suggestion for future work.