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High-Dimensional Statistical Models ...

Ge, Yawei,

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High-Dimensional Statistical Models and Hypothesis Tests With a Focus on Forensic and Genetic Applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	High-Dimensional Statistical Models and Hypothesis Tests With a Focus on Forensic and Genetic Applications // Yawei Ge.
Author:	Ge, Yawei,
Description:	1 electronic resource (97 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-12, Section: A.
Contained By:	Dissertations Abstracts International85-12A.
Subject:	Statistics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30994522
ISBN:	9798382800721

High-Dimensional Statistical Models and Hypothesis Tests With a Focus on Forensic and Genetic Applications /
Ge, Yawei,

High-Dimensional Statistical Models and Hypothesis Tests With a Focus on Forensic and Genetic Applications /Yawei Ge. - 1 electronic resource (97 pages)

Source: Dissertations Abstracts International, Volume: 85-12, Section: A.

We consider the applications of statistical methods in the field of forensic science and genetic science, where we are able to record more and better traits from the study objects as the advance of modern technology. In forensic science, we are moving from the traditional microscope comparisons to 3D scans with computer based algorithms in response to the need of objective methods. We propose beta-mixture distributions to model the cross-correlation functions (CCF) for matching and non-matching bullets, and further apply the score-based likelihood ratios to quantify the strength of evidence. We also propose a screening procedure and analyze the use of reference database which improves the performance of prediction. In genetic science, we analyze the experiment data which is designed to understand the underlying relations among biomass, metabolites, microbiome, genotypes of sorghum and levels of nitrogen. The recorded number of microbiome and metabolites by advanced measurement technology is larger than the sample size, which is known as the "large p, small n" scenario. We propose a high-dimensional linear mixed effect model to quantify the effect of multiple groups of factors to biomass. Further, we propose a high-dimensional test procedure to conduct the simultaneous test of coefficients while controlling a group of high-dimensional nuisance variables to replace the conventional F-test. We show the properties of the proposed test statistic through theorems and simulations.

English

ISBN: 9798382800721Subjects--Topical Terms:

517247
Statistics.
Subjects--Index Terms:

High-dimensional test

High-Dimensional Statistical Models and Hypothesis Tests With a Focus on Forensic and Genetic Applications /
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502 $b Ph.D. $c Iowa State University $d 2024.
520 $a We consider the applications of statistical methods in the field of forensic science and genetic science, where we are able to record more and better traits from the study objects as the advance of modern technology. In forensic science, we are moving from the traditional microscope comparisons to 3D scans with computer based algorithms in response to the need of objective methods. We propose beta-mixture distributions to model the cross-correlation functions (CCF) for matching and non-matching bullets, and further apply the score-based likelihood ratios to quantify the strength of evidence. We also propose a screening procedure and analyze the use of reference database which improves the performance of prediction. In genetic science, we analyze the experiment data which is designed to understand the underlying relations among biomass, metabolites, microbiome, genotypes of sorghum and levels of nitrogen. The recorded number of microbiome and metabolites by advanced measurement technology is larger than the sample size, which is known as the "large p, small n" scenario. We propose a high-dimensional linear mixed effect model to quantify the effect of multiple groups of factors to biomass. Further, we propose a high-dimensional test procedure to conduct the simultaneous test of coefficients while controlling a group of high-dimensional nuisance variables to replace the conventional F-test. We show the properties of the proposed test statistic through theorems and simulations.
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650 4 $a Microbiology. $3 536250
650 4 $a Forensic sciences. $3 606870
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653 $a High-dimensional test
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653 $a 3D scans
653 $a Genetic application
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710 2 $a Iowa State University. $b Statistics. $e degree granting institution. $3 3819198
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720 1 $a Qiu, Yumou $e degree supervisor.
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