bayesian implementation fundamentals of pure and applied economics

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Bayesian Implementation

Author : T. Palfrey
ISBN : 9781136458859
Genre : Business & Economics
File Size : 78. 54 MB
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The authors present a basic model of the Bayesian implementation problem and then consider its application in areas including classical pure exchange economies, public goods provision, auctions and bargaining.

The Theory Of Implementation Of Socially Optimal Decisions In Economics

Author : L. Corchon
ISBN : 9780230372832
Genre : Business & Economics
File Size : 59. 46 MB
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Since the early seventies, following the pioneering work by Leo Hurwicz, economists have been studying the relationship between socially optimal goals and private self-interest. The task was to reconcile the Utopian and Hobbesian traditions, using game theory to find ways to organise the society that are both socially optimal and incentive compatible. This book provides a succinct and up-to-date account of this vast literature and will be welcomed by students, lecturers and anyone wishing to update their knowledge of the field.

Advances In Economic Theory Volume 1

Author : Econometric Society. World Congress
ISBN : 0521484596
Genre : Business & Economics
File Size : 32. 61 MB
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These books comprise papers examining the latest developments in economic theory given at the Sixth World Congress of the Econometric Society in Barcelona in August 1990. They are the latest in a series of collections that cover the most active fields in economic theory over a five year period. With papers from the world's leading specialists, the books give the reader a unique survey of the most recent advances in economic theory.

Harwood Fundamentals Of Pure And Applied Economics

Author : J. Lesourne
ISBN : 0415269075
Genre : Business & Economics
File Size : 21. 39 MB
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The Harwood Fundamentals of Pure and Applied Economics series was a groundbreaking attempt to provide a comprehensive overview of modern economics. A series of short books - arranged into thematic sections - provides state-of-the-art accounts of key areas within the discipline. Although never completed, the series produced several landmark books. It is notable for: * charting the emergence of vibrant new areas of economics (eg 'positive' political economy) * the numerous examples it gives of major innovations like game theory and the new institutional economics re-vitalizing traditional areas of economics * attracting some of the most talented economists of its generation, including Avinash Dixit, Drew Fudenberg, Thomas Palfrey and Jean Tirole This collection reprints the series in its entirety, making all titles available in hardback for the first time, either as individual volumes, or bound together in mini-sets organized by sub-discipline.

Essays On Matching Implementation Theory

Author : Kim-Sau Chung
ISBN : WISC:89063583306
Genre :
File Size : 21. 20 MB
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Whitaker S Books In Print

Author :
ISBN : UOM:39015045631895
Genre : Bibliography, National
File Size : 53. 21 MB
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On Robust Constitution Design

Author : Emmanuelle Auriol
ISBN : UVA:X004529803
Genre : Constitutions
File Size : 56. 49 MB
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The British National Bibliography

Author : Arthur James Wells
ISBN : UOM:39015079755784
Genre : English literature
File Size : 71. 85 MB
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Papers And Proceedings Of The Annual Meeting

Author : American Economic Association. Meeting
ISBN : STANFORD:36105016712726
Genre : Economics
File Size : 80. 1 MB
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Bayesian Methods For Hackers

Author : Cameron Davidson-Pilon
ISBN : 9780133902921
Genre : Computers
File Size : 46. 46 MB
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Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

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