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Full article: Projection Test for Mean Vector in High Dimensions
Source: tandfonline.com
Article summary:
1. The article discusses the problem of testing whether a population mean equals a known vector or the equality of means from two populations in high-dimensional statistics.
2. Three types of tests have been proposed for high-dimensional mean vectors: quadratic-form tests, extreme-type tests, and projection tests.
3. The article examines the open questions remaining to be addressed regarding optimal direction based projection tests, such as how to obtain a good estimation of the optimal projection with statistical guarantees.
Article analysis:
The article is generally reliable and trustworthy in its discussion of testing whether a population mean equals a known vector or the equality of means from two populations in high-dimensional statistics. It provides an overview of three types of tests that have been proposed for this purpose, as well as open questions that remain to be addressed regarding optimal direction based projection tests. The article cites relevant research papers to support its claims, which adds credibility to its arguments.
However, there are some potential biases and one-sided reporting present in the article. For example, it only focuses on three types of tests without exploring other possible methods or approaches that could be used for this purpose. Additionally, while it does cite relevant research papers to support its claims, it does not provide any evidence for the claims made beyond citing these papers. Furthermore, it does not explore any counterarguments or present both sides equally when discussing different types of tests; instead it focuses solely on their advantages without noting any potential risks or drawbacks associated with them. Finally, there is no promotional content present in the article which could lead readers to believe that one type of test is superior over another without providing sufficient evidence for this claim.
In conclusion, while the article is generally reliable and trustworthy in its discussion of testing whether a population mean equals a known vector or the equality of means from two populations in high-dimensional statistics, there are some potential biases and one-sided reporting present which should be noted by readers before drawing conclusions from its arguments.