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 Free Download Marie Winn, "Red-Tails in Love: A Wildlife Drama in Central Park" English | 2005 | ISBN: 0679758461, 0679439978 | EPUB | pages: 352 | 2.6 mb Updated Edition-Ten Years Later  Paolo Simonetti, Umberto Rossi, "Dream Tonight of Peacock Tails: Essays on the Fiftieth Anniversary of Thomas Pynchon's V" English | 2015 | ISBN: 1443877670 | PDF | pages: 223 | 2.8 mb Dream Tonight of Peacock Tails marks the first in-depth examination of Pynchon s debut novel, which was immediately recognized as a breakthrough masterpiece. The eight essays collected in the volume provide both scholars and avid readers with new and original insights into a too-often underestimated work that, probably even more than Gravity s Rainbow, established Pynchon as one of the great masters of twentieth-century American literature. This book deliberately privileges a multidisciplinary and transnational approach, encompassing collaborations from a particularly international and diverse academic context. As such, this volume offers a multifaceted pattern of expanding investigation that tackles the novel s apparently chaotic but meticulously organized structure by rereading it in the light of recent US and European history and economics, as well as by exploring its many real and imagined locations. Not only are the essays brought together here revelatory of Pynchon s way of working, but they also tell us something about our own ways of approaching his fiction.
 Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications (Technical Incerto) by Nassim Nicholas Taleb English | June 30, 2020 | ISBN: 1544508050 | 446 pages | EPUB | 11 Mb The book investigates the misapplication of conventional statistical techniques to fat tailed distributions and looks for remedies, when possible. Switching from thin tailed to fat tailed distributions requires more than "changing the color of the dress." Traditional asymptotics deal mainly with either n=1 or n=∞, and the real world is in between, under the "laws of the medium numbers"-which vary widely across specific distributions. Both the law of large numbers and the generalized central limit mechanisms operate in highly idiosyncratic ways outside the standard Gaussian or Levy-Stable basins of convergence. A few examples: - The sample mean is rarely in line with the population mean, with effect on "naïve empiricism," but can be sometimes be estimated via parametric methods. - The "empirical distribution" is rarely empirical. - Parameter uncertainty has compounding effects on statistical metrics. - Dimension reduction (principal components) fails. - Inequality estimators (Gini or quantile contributions) are not additive and produce wrong results. - Many "biases" found in psychology become entirely rational under more sophisticated probability distributions. - Most of the failures of financial economics, econometrics, and behavioral economics can be attributed to using the wrong distributions. |
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