Detection of Sparse and Weak Effects in High-Dimensional Supervised Learning Problems, Applied to Human Microbiome Data

Detection of Sparse and Weak Effects in High-Dimensional Supervised Learning Problems, Applied to Human Microbiome Data

This project studies the signal detection and identification problem in high-dimensional noisy data and the possibility of using it on microbiome data. An extensive simulation study was performed on generated data using as well as a microbiome dataset collected on patients with Parkinson's dise...

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Bibliographic Details
Main Author: Lindahl, Fred
Format: Others
Language:English
Published: KTH, Matematisk statistik 2020
Subjects:
Signal detection
signal identification
higher criticism
microbiome data
sparse and weak effects
goodness-of-fit tests
kolmogorov-smirnov tests
Signal detektering
signal identifiering
mikrobiom data
glesa och svaga effekter
goodness-of-fit tester
Kolmogorov-smirnov tester
Probability Theory and Statistics
Sannolikhetsteori och statistik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288503

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288503

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