University of Rochester

About: University of Rochester is a education organization based out in Rochester, New York, United States. It is known for research contribution in the topics: Population & Laser. The organization has 63915 authors who have published 112762 publications receiving 5484122 citations. The organization is also known as: Rochester University.

Endogeneity in Empirical Corporate Finance1

Abstract: This chapter discusses how applied researchers in corporate finance can address endogeneity concerns. We begin by reviewing the sources of endogeneity—omitted variables, simultaneity, and measurement error—and their implications for inference. We then discuss in detail a number of econometric techniques aimed at addressing endogeneity problems, including instrumental variables, difference-in-differences estimators, regression discontinuity design, matching methods, panel data methods, and higher order moments estimators. The unifying themes of our discussion are the emphasis on intuition and the applications to corporate finance.

Supernormal vision and high-resolution retinal imaging through adaptive optics

Abstract: Even when corrected with the best spectacles or contact lenses, normal human eyes still suffer from monochromatic aberrations that blur vision when the pupil is large. We have successfully corrected these aberrations using adaptive optics, providing normal eyes with supernormal optical quality. Contrast sensitivity to fine spatial patterns was increased when observers viewed stimuli through adaptive optics. The eye's aberrations also limit the resolution of images of the retina, a limit that has existed since the invention of the ophthalmoscope. We have constructed a fundus camera equipped with adaptive optics that provides unprecedented resolution, allowing the imaging of microscopic structures the size of single cells in the living human retina.

Comparison of warfarin and aspirin for symptomatic intracranial arterial stenosis

Abstract: methods We randomly assigned patients with transient ischemic attack or stroke caused by angiographically verified 50 to 99 percent stenosis of a major intracranial artery to receive warfarin (target international normalized ratio, 2.0 to 3.0) or aspirin (1300 mg per day) in a double-blind, multicenter clinical trial. The primary end point was ischemic stroke, brain hemorrhage, or death from vascular causes other than stroke. results After 569 patients had undergone randomization, enrollment was stopped because of concerns about the safety of the patients who had been assigned to receive warfarin. During a mean follow-up period of 1.8 years, adverse events in the two groups included death (4.3 percent in the aspirin group vs. 9.7 percent in the warfarin group; hazard ratio for aspirin relative to warfarin, 0.46; 95 percent confidence interval, 0.23 to 0.90; P=0.02), major hemorrhage (3.2 percent vs. 8.3 percent, respectively; hazard ratio, 0.39; 95 percent confidence interval, 0.18 to 0.84; P=0.01), and myocardial infarction or sudden death (2.9 percent vs. 7.3 percent, respectively; hazard ratio, 0.40; 95 percent confidence interval, 0.18 to 0.91; P=0.02). The rate of death from vascular causes was 3.2 percent in the aspirin group and 5.9 percent in the warfarin group (P=0.16); the rate of death from nonvascular causes was 1.1 percent and 3.8 percent, respectively (P=0.05). The primary end point occurred in 22.1 percent of the patients in the aspirin group and 21.8 percent of those in the warfarin group (hazard ratio, 1.04; 95 percent confidence interval, 0.73 to 1.48; P=0.83). conclusions Warfarin was associated with significantly higher rates of adverse events and provided no benefit over aspirin in this trial. Aspirin should be used in preference to warfarin for patients with intracranial arterial stenosis.

The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations

Abstract: This article and the associated data and programs provided with it are intended to assist color engineers and scientists in correctly implementing the recently developed CIEDE2000 color-difference formula. We indicate several potential implementation errors that are not uncovered in tests performed using the original sample data published with the standard. A supplemental set of data is provided for comprehensive testing of implementations. The test data, Microsoft Excel spreadsheets, and MATLAB scripts for evaluating the CIEDE2000 color difference are made available at the first author's website. Finally, we also point out small mathematical discontinuities in the formula. © 2004 Wiley Periodicals, Inc. Col Res Appl, 30, 21–30, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20070

Bayesian inference with probabilistic population codes.

Abstract: Recent psychophysical experiments indicate that humans perform near-optimal Bayesian inference in a wide variety of tasks, ranging from cue integration to decision making to motor control. This implies that neurons both represent probability distributions and combine those distributions according to a close approximation to Bayes' rule. At first sight, it would seem that the high variability in the responses of cortical neurons would make it difficult to implement such optimal statistical inference in cortical circuits. We argue that, in fact, this variability implies that populations of neurons automatically represent probability distributions over the stimulus, a type of code we call probabilistic population codes. Moreover, we demonstrate that the Poisson-like variability observed in cortex reduces a broad class of Bayesian inference to simple linear combinations of populations of neural activity. These results hold for arbitrary probability distributions over the stimulus, for tuning curves of arbitrary shape and for realistic neuronal variability.