How Long to Read Large Sample Covariance Matrices and High-Dimensional Data Analysis

How Long Does it Take to Read Large Sample Covariance Matrices and High-Dimensional Data Analysis?

It takes the average reader to read Large Sample Covariance Matrices and High-Dimensional Data Analysis by Jianfeng Yao

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Description

High-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that several well-known methods in multivariate analysis become inefficient, or even misleading, when the data dimension p is larger than, say, several tens. A seminal example is the well-known inefficiency of Hotelling's T2-test in such cases. This example shows that classical large sample limits may no longer hold for high-dimensional data; statisticians must seek new limiting theorems in these instances. Thus, the theory of random matrices (RMT) serves as a much-needed and welcome alternative framework. Based on the authors' own research, this book provides a first-hand introduction to new high-dimensional statistical methods derived from RMT. The book begins with a detailed introduction to useful tools from RMT, and then presents a series of high-dimensional problems with solutions provided by RMT methods.

How long is Large Sample Covariance Matrices and High-Dimensional Data Analysis?

Large Sample Covariance Matrices and High-Dimensional Data Analysis by Jianfeng Yao is 0 pages long, and a total of 0 words.

This makes it 0% the length of the average book. It also has 0% more words than the average book.

How Long Does it Take to Read Large Sample Covariance Matrices and High-Dimensional Data Analysis Aloud?

The average oral reading speed is 183 words per minute. This means it takes to read Large Sample Covariance Matrices and High-Dimensional Data Analysis aloud.

What Reading Level is Large Sample Covariance Matrices and High-Dimensional Data Analysis?

Large Sample Covariance Matrices and High-Dimensional Data Analysis is suitable for students ages 2 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

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