Edited by Yorghos Apostolopoulos, Michael K. Lemke, and Kristen Hassmiller Lich

 

• The first comprehensive book integrating complex systems theory, methodology and modeling, with current population health practices
• An instructional primer including learning objectives, take-home messages, and resources for further reading
• Makes complex systems approachable for university professors, graduate students, policymakers, researchers, and practitioners of population health

Source: global.oup.com

A clear, concise introduction to the quickly growing field of complexity science that explains its conceptual and mathematical foundations

What is a complex system? Although “complexity science” is used to understand phenomena as diverse as the behavior of honeybees, the economic markets, the human brain, and the climate, there is no agreement about its foundations. In this introduction for students, academics, and general readers, philosopher of science James Ladyman and physicist Karoline Wiesner develop an account of complexity that brings the different concepts and mathematical measures applied to complex systems into a single framework. They introduce the different features of complex systems, discuss different conceptions of complexity, and develop their own account. They explain why complexity science is so important in today’s world.

Source: yalebooks.yale.edu

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 of 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 "naive 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.
This book, the first volume of the Technical Incerto, weaves a narrative around published journal articles.

Source: www.researchers.one

This book aims to contribute to the overall, integrated understanding of the processes of language contact and their evolution, be they the result of political or economic (dis)integrations or migrations or for technological reasons. Via an interdisciplinary, holistic approach, it also aims to support the theoretical grounding of a unified, common sociolinguistic paradigm, based on an ecological and complexity perspective. This approach built on the fact that linguistic structures do not live in isolation from their social functions and must be situated in relation to the sub-and supra-systems that determine their existence if we are to understand their fortunes. It is a useful contribution to understanding and promoting the processes of linguistic revitalization in the world, combining at the same time the maintenance and development of diversity while ensuring the intercommunication of human species.

Source: www.publicacions.ub.edu