Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

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ID: 288162
2016
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Abstract
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
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persistent_1761420406_68fd247600173 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Trevor Hastie
Journal ADVANCES IN ARCHAEOLOGICAL PRACTICE
Year 2016
DOI
10.1017/CBO9781316576533
URL
Keywords Keywords not found

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