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A New Test of Independence and Its Application to Variable Selection

Moon, Haeun (2022) A New Test of Independence and Its Application to Variable Selection. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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In the first part of our research, we propose a new interpoint-ranking sign covariance
measure for nonparametric test of independence. The proposed method is applicable to
general types of random objects as long as a meaningful similarity measure can be defined,
and it is shown to be zero if and only if the two random variables are independent. The
test statistic is a U-statistic, whose large sample behavior guarantees that the proposed
test is consistent against general types of alternatives. Numerical experiments and data
analyses demonstrate the great empirical performance of the proposed method. In the second
part, we propose to combine the frequent voting idea with the proposed and existing
test of independence methods for model-free variable selection. This research is motivated
and illustrated by an application in selecting important genes related to suicidal behaviors.
Numerical experiments demonstrate nice empirical performance of the proposed method.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Moon, Haeunham98@pitt.eduham98
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairChen, Kehuikhchen@pitt.edukhchen
Committee MemberCheng, Yuyucheng@pitt.eduyucheng
Committee MemberRen, Zhaozren@pitt.eduzren
Committee MemberDing, Yingyingding@pitt.eduyingding
Date: 12 October 2022
Date Type: Publication
Defense Date: 25 April 2022
Approval Date: 12 October 2022
Submission Date: 4 August 2022
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 75
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Statistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Consistent; Independence Test; Interpoint distance; Nonparametric; Sign Covariance;Model-free selection.
Date Deposited: 12 Oct 2022 15:25
Last Modified: 12 Oct 2022 15:25


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