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        <datestamp>2023-07-11</datestamp>
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          <dc:contributor>Shao, Xiaofeng</dc:contributor>
          <dc:contributor>Shao, Xiaofeng</dc:contributor>
          <dc:contributor>Simpson, Douglas</dc:contributor>
          <dc:contributor>Li, Bo</dc:contributor>
          <dc:contributor>Chen, Xiaohui</dc:contributor>
          <dc:creator>Lee, Chung Eun</dc:creator>
          <dc:date>2017-09-29T17:45:39Z</dc:date>
          <dc:date>2017-09-29T17:45:39Z</dc:date>
          <dc:date>2020-03-03T10:15:25Z</dc:date>
          <dc:date>2017-06-30</dc:date>
          <dc:date>2017-08</dc:date>
          <dc:description>In this thesis, we focus on inference problems for time series and functional data and develop new methodologies by using new dependence metrics which can be viewed as an extension of Martingale Diﬀerence Divergence (MDD) [see Shao and Zhang (2014)] that quantiﬁes the conditional mean dependence of two random vectors. For one part, the new approaches to dimension reduction of multivariate time series for conditional mean and conditional variance are proposed by applying new metrics, the so-called Martingale Diﬀerence Divergence Matrix (MDDM), Volatility Martingale Diﬀerence Divergence (VMDDM), and vec Volatility Martingale Diﬀerence Divergence (vecVMDDM). For the other part, we propose a nonparametric conditional mean independence test for a response variable Y given a covariate variable X, both of which can be function-valued or vector-valued. The test is built upon Functional Martingale Diﬀerence Divergence (FMDD) which fully measures the conditional mean independence of Y on X.</dc:description>
          <dc:description>Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-08-01</dc:description>
          <dc:description>The student, Chung Eun Lee, accepted the attached license on 2017-06-28 at 13:05.</dc:description>
          <dc:description>The student, Chung Eun Lee, submitted this Dissertation for approval on 2017-06-28 at 13:26.</dc:description>
          <dc:description>This Dissertation was approved for publication on 2017-06-30 at 14:37.</dc:description>
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  Previous issue date: 2017-06-30</dc:description>
          <dc:description>Embargo set by: Colleen Fallaw for item 103489
Lift date: 2019-09-29T17:48:06Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system</dc:description>
          <dc:description>Embargo set by: Seth Robbins for item 103489
Lift date: 2020-03-02T19:56:41Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system</dc:description>
          <dc:description>Embargo set by: Seth Robbins for item 103489
Lift date: 2020-03-02T19:59:52Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system</dc:description>
          <dc:description>Embargo set by: Seth Robbins for item 103489
Lift date: 2020-03-02T20:02:46Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system</dc:description>
          <dc:description>U of I Only Restriction Lifted for Item 103489 on 2020-03-03T10:15:25Z.</dc:description>
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          <dc:identifier>http://hdl.handle.net/2142/98188</dc:identifier>
          <dc:language>en</dc:language>
          <dc:rights>Copyright 2017 Chung Eun Lee</dc:rights>
          <dc:subject>Conditional mean</dc:subject>
          <dc:subject>Dimension reduction</dc:subject>
          <dc:subject>Nonlinear dependence</dc:subject>
          <dc:title>Statistical inference of multivariate time series and functional data using new dependence metrics</dc:title>
          <dc:type>text</dc:type>
          <dc:type>text</dc:type>
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            <department>Statistics</department>
            <discipline>Statistics</discipline>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <level>Dissertation</level>
            <name>Ph.D.</name>
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