
The Elements of Statistical Learning
by Trevor Hastie, Robert Tibshirani, Jerome Friedman (2001)
Like 'Computer Age Statistical Inference', this book offers a foundational understanding of statistical learning methods.

by Bradley Efron, Trevor Hastie (2016)
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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by Trevor Hastie, Robert Tibshirani, Jerome Friedman (2001)
Like 'Computer Age Statistical Inference', this book offers a foundational understanding of statistical learning methods.

by Richard McElreath (2015)
Similar to 'Computer Age Statistical Inference', this book delves into generalized linear models with intuitive explanations.

by Julian J. Faraway (2005)
Like 'Computer Age Statistical Inference', this book provides R code examples for advanced statistical modeling.

by Frank E. Harrell Jr. (2015)
This book, similar to 'Computer Age Statistical Inference', offers in-depth explanations of regression and survival modeling.

by David G. Kleinbaum (2005)
Echoing 'Computer Age Statistical Inference', this text provides straightforward explanations and R examples for survival analysis.
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