Abstract Details
Activity Number:
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287
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Type:
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Invited
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Date/Time:
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Tuesday, August 11, 2015 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract #314472
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Title:
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Statistical Inference for Complex Data Objects
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Author(s):
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Haonan Wang* and Ela Sienkiewicz
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Companies:
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Colorado State University and Colorado State University
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Keywords:
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Binary Tree ;
Object Oriented Data Analysis ;
Topology
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Abstract:
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In the big data era, complex data objects are frequently collected in various scientific fields. Our motivating example is a data set of brain neurons. Each neuron can be modeled as a tree-structured data object with both topological and geometric properties. Statistical inference concerning the distribution of such data objects is of great interest. We formulate the estimation problem as a multi-objective optimization which balances the tradeoff among various measures of the topological and geometric properties of complex data objects. Some preliminary results using real data examples will be discussed.
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Authors who are presenting talks have a * after their name.
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