Computer Age Statistical Inference 2025 pdf epub mobi 电子书

☆☆☆☆☆
简体网页||繁体网页

Computer Age Statistical Inference 2025 pdf epub mobi 电子书著者简介

Bradley Efron, Stanford University, California

Bradley Efron is Max H. Stein Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University, California. He has held visiting faculty appointments at Harvard University, Massachusetts, the University of California, Berkeley, and Imperial College of Science, Technology and Medicine, London. Efron has worked extensively on theories of statistical inference, and is the inventor of the bootstrap sampling technique. He received the National Medal of Science in 2005 and the Guy Medal in Gold of the Royal Statistical Society in 2014.

Trevor Hastie, Stanford University, California

Trevor Hastie is John A. Overdeck Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University, California. He is coauthor of Elements of Statistical Learning, a key text in the field of modern data analysis. He is also known for his work on generalized additive models and principal curves, and for his contributions to the R computing environment. Hastie was awarded the Emmanuel and Carol Parzen prize for Statistical Innovation in 2014.

Computer Age Statistical Inference 电子书图书目录

下载链接在页面底部

下载链接1
下载链接2
下载链接3

facebook linkedin mastodon messenger pinterest reddit telegram twitter viber vkontakte whatsapp 复制链接

想要找书就要到本本书屋

onlinetoolsland.com

立刻按 ctrl+D收藏本页

你会得到大惊喜!!

发表于2025-02-07

Computer Age Statistical Inference 2025 pdf epub mobi 电子书

喜欢 Computer Age Statistical Inference 电子书的读者还喜欢

Computer Age Statistical Inference 电子书读后感

评分☆☆☆☆☆

类似图书点击查看全场最低价

出版者:Cambridge University Press

作者:Bradley Efron

出品人:

页数:495

译者:

出版时间:2016-7-21

价格:USD 74.99

装帧:Hardcover

isbn号码:9781107149892

丛书系列:

图书标签: 统计学统计数据科学计算机 statistics Statistics 算法統計學

Computer Age Statistical Inference 2025 pdf epub mobi 电子书图书描述

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.

Clarifies both traditional methods and current, popular algorithms (e.g. neural nets, random forests)

Written by two world-leading researchers

Addressed to all fields that work with data

Computer Age Statistical Inference 2025 pdf epub mobi 电子书

想要找书就要到本本书屋

onlinetoolsland.com

立刻按 ctrl+D收藏本页

你会得到大惊喜!!