The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. '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? How does it all fit together? Now in p...(展开全部)

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 ...(展开全部)

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 ...(展开全部)

This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be use...(展开全部)

This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be use...(展开全部)

Casella 在福特汉姆大学完成了他的本科教育，在普渡大学完成了研究生教育。他曾在罗格斯大学、康奈尔大学和佛罗里达大学任教。他的贡献集中在统计学领域，包括蒙特卡洛方法、模型选择和基因组分析。他在贝叶斯和经验贝叶斯方法方面特别活跃，其作品与斯坦因现象相联系，涉及评估和加速马尔科夫链蒙特卡洛方法的收敛性，如他的Rao-Blackwellisation技术，以及将拉索重塑为具有独立拉普拉斯先验的贝叶斯后验模式估计。 Casella于1988年被任命为美国统计学会和数学统计研究所的研究员，并于1989年成为国际统计学会的当选研究员。2009年，他被任命为西班牙皇家科学院外籍院士。 Roger Lee Berger 是美国统计学家和教授，与合作者 George Casella 于1990年首次出版《Statistical Inference》一书。

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences abou...(展开全部)

WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory...(展开全部)

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mat...(展开全部)

WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory...(展开全部)