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University of California, Los Angeles. Statistics 0891. degree granting institution.

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Iowa State University. Statistics. degree granting institution.

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The University of North Carolina at Chapel Hill. Biostatistics. degree granting institution.

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University of Maryland, College Park. Mathematical Statistics. degree granting institution.

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University of South Carolina. Statistics. degree granting institution.

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Ananth, Varsha, author.

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Baek, Seungchul, author.

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Barkley, Brian G., author.

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Berchuck, Samuel L., author.

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Carnegie Mellon University. Electrical and Computer Engineering. degree granting institution.

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Chen, Jie, author.

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Cheng, Edward K., author.

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Clemson University. Mathematical Science. degree granting institution.

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Columbia University. Statistics. degree granting institution.

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Delaware State University. Computer Sciences. degree granting institution.

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Demirdjian, Levon, author.

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Du, Chengan, author.

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Gao, Christian Siyao, author.

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George Mason University. Computational Sciences and Informatics. degree granting institution.

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George Mason University. Statistical Science. degree granting institution.

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Girard, Agathe, author.

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Green, Michael A., author.

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Hammuda, Muna Mohamed, author.

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Harris, Richard T., author.

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Hellams, Luvenia Nicole, author.

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Iowa State University. Industrial and Manufacturing Systems Engineering. degree granting institution.

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Kaukis, Nicholas Armstrong, author.

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Koyily, Anoop, author.

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Li, Quan, author.

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Li, Yihua, author.

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Ma, Chong, author.

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Massachusetts Institute of Technology. degree granting institution.

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Michigan Technological University. Mathematical Sciences. degree granting institution.

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Mittman, Eric T., author.

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Moon, Jessie Eunyoung, author.

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Ng, Carmen Doris, author.

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Nguyen, Son, author.

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Ohio University. Mathematics (Arts and Sciences). degree granting institution.

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Oklahoma State University. Statistics. degree granting institution.

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Purdue University. Computer Sciences. degree granting institution.

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Rigsby, John Thomas, III, author. (orcid)0000-0001-5393-5270

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Rosenberg, Joshua B., author.

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Semedo, Joao D., author.

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Shao, Kanghong, author.

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State University of New York at Binghamton. Systems Science Industrial Engineering. degree granting institution.

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Tan, Xi, author.

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The University of Chicago. Statistics. degree granting institution.

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The University of Wisconsin - Madison. Statistics. degree granting institution.

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Thomas, April L., author.

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Tzougas, John George, author.

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University of California, Los Angeles. Statistics. degree granting institution.

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Wake Forest University. Mathematics and Statistics. degree granting institution.

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Wong, Sze Wai, author.

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Woytarowicz, Nicole, author.

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Xie, Meihui, author.

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Yao, Xuan, author.

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Cover image for The mathematical theory of optimal linear regression design

The mathematical theory of optimal linear regression design

1.

The mathematical theory of optimal linear regression design

by

Tzougas, John George, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10868014

Format:

Excerpt:

concave criterion function &phis;. A summary is given of relevant known work in the theory of optimal

Cover image for Dimension Reduction for Classification with Many Covariates and Pathway Activity Level Estimation

Dimension Reduction for Classification with Many Covariates and Pathway Activity Level Estimation

2.

Dimension Reduction for Classification with Many Covariates and Pathway Activity Level Estimation

by

Baek, Seungchul, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10786058

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Excerpt:

in this work present contributions to classification and pathway activity estimation: (1) we propose

Cover image for Statistical Models for Cognitive Social Structures

Statistical Models for Cognitive Social Structures

3.

Statistical Models for Cognitive Social Structures

by

Shao, Kanghong, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10829462

Format:

Excerpt:

by this work, we modify the model to characterize cognitive social structures by adding a parameter

Cover image for Selected Legal Applications for Bayesian Methods

Selected Legal Applications for Bayesian Methods

4.

Selected Legal Applications for Bayesian Methods

by

Cheng, Edward K., author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10830769

Format:

Excerpt:

the fees. The methods proposed have lower informational requirements than previous work and appear to

Cover image for Using Bayesian Hierarchical Models to Study the Spatial and Temporal Distribution of Mammals in Serengeti National Park

Using Bayesian Hierarchical Models to Study the Spatial and Temporal Distribution of Mammals in Serengeti National Park

5.

Using Bayesian Hierarchical Models to Study the Spatial and Temporal Distribution of Mammals in Serengeti National Park

by

Harris, Richard T., author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10750571

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Excerpt:

depending on the time interval, then we extend our work to study the dependence between two species.

Cover image for Utilizing Observations and Ranks in Kernel Estimation

Utilizing Observations and Ranks in Kernel Estimation

6.

Utilizing Observations and Ranks in Kernel Estimation

by

Kaukis, Nicholas Armstrong, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10245457

Format:

Excerpt:

-parametric setting. However, observations and ranks can be utilized simultaneously. This work concentrates on

Cover image for Estimating Animal Abundance by Employing an External Experiment to Account for Detection and Count Bias with an Application to Wintering Ducks in the Mississippi Alluvial Valley

Estimating Animal Abundance by Employing an External Experiment to Account for Detection and Count Bias with an Application to Wintering Ducks in the Mississippi Alluvial Valley

7.

Estimating Animal Abundance by Employing an External Experiment to Account for Detection and Count Bias with an Application to Wintering Ducks in the Mississippi Alluvial Valley

by

Thomas, April L., author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10792528

Format:

Excerpt:

parameters being used to adjust for visibility bias. This work considers a bias adjusted estimator, proposed

Cover image for Bayesian Nonparametrics to Model Content, User, and Latent Structure in Hawkes Processes

Bayesian Nonparametrics to Model Content, User, and Latent Structure in Hawkes Processes

8.

Bayesian Nonparametrics to Model Content, User, and Latent Structure in Hawkes Processes

by

Tan, Xi, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10793142

Format:

Excerpt:

characteristics have been largely ignored in previous work. In this dissertation, we address these limitations via

Cover image for Feature Selection and Classification for High-Dimensional Biological Data Under Cross-Validation Framework

Feature Selection and Classification for High-Dimensional Biological Data Under Cross-Validation Framework

9.

Feature Selection and Classification for High-Dimensional Biological Data Under Cross-Validation Framework

by

Zhong, Yi, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10817332

Format:

Excerpt:

methods. We have summarized our work in the following order: (1) the structure of high dimensional

Cover image for Applications of Bayesian Hierarchical Models in Gene Expression and Product Reliability

Applications of Bayesian Hierarchical Models in Gene Expression and Product Reliability

10.

Applications of Bayesian Hierarchical Models in Gene Expression and Product Reliability

by

Mittman, Eric T., author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10688357

Format:

Excerpt:

inference have been developed. In this work, we present two such models, both motivated by real applications

Cover image for Sharp Thresholds for the Frog Model and Related Systems

Sharp Thresholds for the Frog Model and Related Systems

11.

Sharp Thresholds for the Frog Model and Related Systems

by

Rosenberg, Joshua B., author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10786250

Format:

Excerpt:

, work towards identifying conditions under which the model is recurrent, transient, or neither, in terms

Cover image for Cox-Type Model Validation with Recurrent Event Data

Cox-Type Model Validation with Recurrent Event Data

12.

Cox-Type Model Validation with Recurrent Event Data

by

Hammuda, Muna Mohamed, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10794004

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This work pertains to statistical inference of the regression parameter and the baseline hazard

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