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Title: Distributed Statistical Computation for Comparing Massive Spatiotemporal Datasets

Abstract

We illustrate the use of a computational framework for applying non-parametric statistical methods to the comparison of massive spatiotemporal datasets within a distributed computing environment.

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1390494
Report Number(s):
NREL/PO-6A20-65091
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY, AND ECONOMY; statistics; data mining; nonparametric testing; spatiotemporal; geospatial

Citation Formats

Bush, Brian W, Biagioni, David, Getman, Dan, Inman, Daniel J, and Elmore, Ryan T. Distributed Statistical Computation for Comparing Massive Spatiotemporal Datasets. United States: N. p., 2017. Web.
Bush, Brian W, Biagioni, David, Getman, Dan, Inman, Daniel J, & Elmore, Ryan T. Distributed Statistical Computation for Comparing Massive Spatiotemporal Datasets. United States.
Bush, Brian W, Biagioni, David, Getman, Dan, Inman, Daniel J, and Elmore, Ryan T. Fri . "Distributed Statistical Computation for Comparing Massive Spatiotemporal Datasets". United States. doi:. https://www.osti.gov/servlets/purl/1390494.
@article{osti_1390494,
title = {Distributed Statistical Computation for Comparing Massive Spatiotemporal Datasets},
author = {Bush, Brian W and Biagioni, David and Getman, Dan and Inman, Daniel J and Elmore, Ryan T},
abstractNote = {We illustrate the use of a computational framework for applying non-parametric statistical methods to the comparison of massive spatiotemporal datasets within a distributed computing environment.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Sep 08 00:00:00 EDT 2017},
month = {Fri Sep 08 00:00:00 EDT 2017}
}

Conference:
Other availability
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