Spatio-temporal change of support modeling with R
Spatio-temporal change of support modeling with R
复制标题
使用 R 进行支持建模的时空变化
DOI:
10.1007/s00180-020-01029-4
复制
发表时间:
2021
影响因子:
1.3
通讯作者:
Wikle, Christopher K.
中科院分区:
文献类型:
--
作者:
Raim, Andrew M.;Holan, Scott H.;Bradley, Jonathan R.;Wikle, Christopher K.
Spatio-temporal change of support methods are designed for statistical analysis on spatial and temporal domains which can differ from those of the observed data. Previous work introduced a parsimonious class of Bayesian hierarchical spatio-temporal models, which we refer to as STCOS, for the case of Gaussian outcomes. Application of STCOS methodology from this literature requires a level of proficiency with spatio-temporal methods and statistical computing which may be a hurdle for potential users. The present work seeks to bridge this gap by guiding readers through STCOS computations. We focus on theRcomputing environment because of its popularity, free availability, and high quality contributed packages. Thestcospackage is introduced to facilitate computations for the STCOS model. A motivating application is the American Community Survey (ACS), an ongoing survey administered by the U.S. Census Bureau that measures key socioeconomic and demographic variables for various populations in the United States. The STCOS methodology offers a principled approach to compute model-based estimates and associated measures of uncertainty for ACS variables on customized geographies and/or time periods. We present a detailed case study with ACS data as a guide for change of support analysis inR, and as a foundation which can be customized to other applications.
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影响因子:
2.5
作者:
Wikle, CK;Berliner, LM
通讯作者:
Berliner, LM
DOI:
--
发表时间:
2020
期刊:
影响因子:
--
作者:
H. Wickham;Romain François;Lionel Henry;K. Müller
通讯作者:
K. Müller
DOI:
10.21105/joss.01221
发表时间:
2019
期刊:
J. Open Source Softw.
影响因子:
--
作者:
C. Prener;Charlie Revord
通讯作者:
Charlie Revord
DOI:
10.7275/3628-0a51
发表时间:
2018
期刊:
Cartographica: The International Journal for Geographic Information and Geovisualization
影响因子:
--
作者:
Nelson Mileu;M. Queirós
通讯作者:
M. Queirós
影响因子:
1.9
作者:
Fuentes, Montserrat;Song, Hae-Ryoung;Davis, Jerry M.
通讯作者:
Davis, Jerry M.