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Representative Points of Statistical Distributions by Fang, Kai-Tai;Ye, Huajun;Zhou, Yongdao; & Ye, Huajun & Zhou, Yongdao is a book available to read on EtoBox.

What is Representative Points of Statistical Distributions about?

Statistical simulation has become a cornerstone in statistical research and applications. The aim of Representative Points of Statistical Distributions: Applications in Statistical Inference is to present a comprehensive exploration of various methods for statistical simulation and resampling, focusing on consistency and efficiency. It covers a range of representative points (RPs)—Monte Carlo (MC) RPs, quasi-Monte Carlo (QMC) RPs, and mean square error (MSE) RPs—and their applications, and includes a collection of recent developments in the field. It also explores other types of representative points and the corresponding approximate distributions, and delves into the realm of statistical simulation by exploring the limitations of traditional MC methods and the innovations brought about by the bootstrap method. In addition, the text introduces other kinds of representative points and the corresponding approximate distributions, such as QMC and MSE methods. Features Comprehensive exploration of statistical simulation methods: provides a deep dive into MC methods and bootstrap methods, and introduces other kinds of RPs and the corresponding approximate distributions, such as QMC and

Author

Fang, Kai-Tai;Ye, Huajun;Zhou, Yongdao; & Ye, Huajun & Zhou, Yongdao

Publisher

CRC Press LLC

Published

2025

Language

EN