High Dimensional Inference – a Literature Review [Articol]
Date
2024
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Abstract
High dimensional inference has been a crucial topic in statistical learning, especially with the rise of data that has a lot of features yet is difficult to gather. We analyze regressions on data in large dimensions p that are much greater than the samples available, n. The usual method in constructing confidence intervals used for OLS is not useful when p » n since asymptotic normality fails. We survey literature that comes up with new method of constructing these intervals.
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Keywords
statistical learning, high-dimensional inference, confidence intervals, lasso
Citation
LOPOTENCO, Alexandru and Marcel TELEUCA. High Dimensional Inference – a Literature Review. In: International Conference dedicated to the 60th anniversary of the foundation of Vladimir Andrunachievici Institute of Mathematics and Computer Science, MSU, October 10-13 2024. Chisinau: [S. n.], 2024, pp. 93-99. ISBN 978-9975-68-515-3