On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm

On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm

Big Data is transforming the way we live. From medical care to social networks, data is playing a central role in various applications. As the volume and dimensionality of datasets keeps growing, designing effective data analytics algorithms emerges as an important research topic in statistics. In t...

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Bibliographic Details
Main Author: Hu, Xinran
Other Authors: Statistics
Format: Others
Published: Virginia Tech 2015
Subjects:
Visual Analytics
Big Data Monte Carlo Sampling
Online Access:http://hdl.handle.net/10919/51224
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spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-512242021-04-24T05:39:58Z On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm Hu, Xinran Statistics Leman, Scotland C. North, Christopher L. Smith, Eric P. House, Leanna L. Visual Analytics Big Data Monte Carlo Sampling Big Data is transforming the way we live. From medical care to social networks, data is playing a central role in various applications. As the volume and dimensionality of datasets keeps growing, designing effective data analytics algorithms emerges as an important research topic in statistics. In this dissertation, I will summarize our research on two data analytics algorithms: a visual analytics algorithm named Grouped Observation Level Interaction with Multidimensional Scaling and a big data Monte Carlo sampling algorithm named Batched Permutation Sampler. These two algorithms are designed to enhance the capability of generating meaningful insights and utilizing massive datasets, respectively. Ph. D. 2015-01-27T09:00:24Z 2015-01-27T09:00:24Z 2015-01-26 Dissertation vt_gsexam:4290 http://hdl.handle.net/10919/51224 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech
collection NDLTD
format Others
sources NDLTD
topic Visual Analytics
Big Data Monte Carlo Sampling
spellingShingle Visual Analytics
Big Data Monte Carlo Sampling
Hu, Xinran
On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm
description Big Data is transforming the way we live. From medical care to social networks, data is playing a central role in various applications. As the volume and dimensionality of datasets keeps growing, designing effective data analytics algorithms emerges as an important research topic in statistics. In this dissertation, I will summarize our research on two data analytics algorithms: a visual analytics algorithm named Grouped Observation Level Interaction with Multidimensional Scaling and a big data Monte Carlo sampling algorithm named Batched Permutation Sampler. These two algorithms are designed to enhance the capability of generating meaningful insights and utilizing massive datasets, respectively. === Ph. D.
author2 Statistics
author_facet Statistics
Hu, Xinran
author Hu, Xinran
author_sort Hu, Xinran
title On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm
title_short On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm
title_full On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm
title_fullStr On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm
title_full_unstemmed On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm
title_sort on grouped observation level interaction and a big data monte carlo sampling algorithm
publisher Virginia Tech
publishDate 2015
url http://hdl.handle.net/10919/51224
work_keys_str_mv AT huxinran ongroupedobservationlevelinteractionandabigdatamontecarlosamplingalgorithm
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