This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics in...(展开全部)

This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics in...(展开全部)

The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both...(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)

"PCT, Spin and Statistics, and All That" is the classic summary of and introduction to the achievements of Axiomatic Quantum Field Theory. This theory gives precise mathematical responses to questions like: What is a quantized field? And what are the physically indispensable attributes of a quantized field? Furthermore, Axiomatic Field Theory shows that a number of physically i...(展开全部)

弗里德曼于 1938 年 3 月 5 日出生于加拿大魁北克省蒙特利尔。他于 1958 年获得麦吉尔大学理学学士学位，并分别于 1959 年和 1960 年获得普林斯顿大学硕士和博士学位。他于 1961 年加入加州大学伯克利分校统计系担任讲师，并于 1962 年被任命为研究员。他的整个职业生涯都在伯克利大学度过。他以概率论者和数理统计学家的身份开始职业生涯，具有贝叶斯倾向，但后来成为世界领先的应用统计学家和谨慎的频率论者之一。

弗里德曼于 1938 年 3 月 5 日出生于加拿大魁北克省蒙特利尔。他于 1958 年获得麦吉尔大学理学学士学位，并分别于 1959 年和 1960 年获得普林斯顿大学硕士和博士学位。他于 1961 年加入加州大学伯克利分校统计系担任讲师，并于 1962 年被任命为研究员。他的整个职业生涯都在伯克利大学度过。他以概率论者和数理统计学家的身份开始职业生涯，具有贝叶斯倾向，但后来成为世界领先的应用统计学家和谨慎的频率论者之一。

This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results are not always given in the most general form but rather under assumptions that lead to shorter or mor...(展开全部)