Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data

Traditional descriptors such as the mean and the covariance matrix give useful global summaries of data and probability measures. Nevertheless, when distributions with more complex topological and geometrical behaviors arise, these methods fall short in accurately describing...

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Other Authors: Díaz Martínez, Diego Hernán (authoraut)
Format: Others
Language:English
English
Published: Florida State University
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Online Access:http://purl.flvc.org/fsu/fd/FSU_2016SP_DiazMartinez_fsu_0071E_13067
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spelling ndltd-fsu.edu-oai-fsu.digital.flvc.org-fsu_3603432020-06-24T03:06:42Z Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data Díaz Martínez, Diego Hernán (authoraut) Mio, Washington (professor directing dissertation) Tschinkel, Walter R. (Walter Reinhart) (university representative) Mesterton-Gibbons, Mike (committee member) Florida State University (degree granting institution) College of Arts and Sciences (degree granting college) Department of Mathematics (degree granting department) Text text Florida State University Florida State University English eng 1 online resource (135 pages) computer application/pdf Traditional descriptors such as the mean and the covariance matrix give useful global summaries of data and probability measures. Nevertheless, when distributions with more complex topological and geometrical behaviors arise, these methods fall short in accurately describing them. This dissertation explores and develops new methods that provide more informative summaries of complex probability measures using multiscale analogs of the Fréchet function and the covariance tensor which encode variation of data with respect to any point in the domain. These multiscale methods are developed using kernel functions and diffusion distances and are helpful in obtaining more information on local-to-regional-to-global behavior of probability measures, unlike the traditional take which only gives global summaries. We applied the methods to the analysis of climatic data of the Fabaceae plant family (legumes) and to microbiome data related to the Clostridium difficile infection in the human gut. Our studies reveal patterns of climatological adaptation of various legume taxa and changes in the interactions of microbial communities in the presence of infection which are helpful in monitoring the resolution of the disease. A Dissertation submitted to the Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Spring Semester 2016. March 17, 2016. climate-plant data, data analysis, microbiome data, multiscale descriptors, probability, statistics Includes bibliographical references. Washington Mio, Professor Directing Dissertation; Walter Tschinkel, University Representative; Richard Bertram, Committee Member; Mike Mesterton-Gibbons, Committee Member. Mathematics FSU_2016SP_DiazMartinez_fsu_0071E_13067 http://purl.flvc.org/fsu/fd/FSU_2016SP_DiazMartinez_fsu_0071E_13067 This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. http://diginole.lib.fsu.edu/islandora/object/fsu%3A360343/datastream/TN/view/Multiscale%20Summaries%20of%20Probability%20Measures%20with%20Applications%20to%20Plant%20and%20Microbiome%20Data.jpg
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language English
English
format Others
sources NDLTD
topic Mathematics
spellingShingle Mathematics
Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data
description Traditional descriptors such as the mean and the covariance matrix give useful global summaries of data and probability measures. Nevertheless, when distributions with more complex topological and geometrical behaviors arise, these methods fall short in accurately describing them. This dissertation explores and develops new methods that provide more informative summaries of complex probability measures using multiscale analogs of the Fréchet function and the covariance tensor which encode variation of data with respect to any point in the domain. These multiscale methods are developed using kernel functions and diffusion distances and are helpful in obtaining more information on local-to-regional-to-global behavior of probability measures, unlike the traditional take which only gives global summaries. We applied the methods to the analysis of climatic data of the Fabaceae plant family (legumes) and to microbiome data related to the Clostridium difficile infection in the human gut. Our studies reveal patterns of climatological adaptation of various legume taxa and changes in the interactions of microbial communities in the presence of infection which are helpful in monitoring the resolution of the disease. === A Dissertation submitted to the Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Spring Semester 2016. === March 17, 2016. === climate-plant data, data analysis, microbiome data, multiscale descriptors, probability, statistics === Includes bibliographical references. === Washington Mio, Professor Directing Dissertation; Walter Tschinkel, University Representative; Richard Bertram, Committee Member; Mike Mesterton-Gibbons, Committee Member.
author2 Díaz Martínez, Diego Hernán (authoraut)
author_facet Díaz Martínez, Diego Hernán (authoraut)
title Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data
title_short Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data
title_full Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data
title_fullStr Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data
title_full_unstemmed Multiscale Summaries of Probability Measures with Applications to Plant and Microbiome Data
title_sort multiscale summaries of probability measures with applications to plant and microbiome data
publisher Florida State University
url http://purl.flvc.org/fsu/fd/FSU_2016SP_DiazMartinez_fsu_0071E_13067
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