An R Package for Generating Covariance Matrices for Maximum-Entropy Sampling from Precipitation Chemistry Data

被引:0
|
作者
Al-Thani H. [1 ]
Lee J. [1 ]
机构
[1] Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, 48109, MI
来源
SN Operations Research Forum | / 1卷 / 3期
关键词
Covariance matrix; Environmental monitoring; Environmetrics; Maximum-entropy sampling; NADP; NTN;
D O I
10.1007/s43069-020-0011-z
中图分类号
学科分类号
摘要
We present an open-source R package (MESgenCov v 0.1.0) for temporally fitting multivariate precipitation chemistry data and extracting a covariance matrix for use in the MESP (maximum-entropy sampling problem). We provide multiple functionalities for modeling and model assessment. The package is tightly coupled with NADP/NTN (National Atmospheric Deposition Program/National Trends Network) data from their set of 379 monitoring sites, 1978–present. The user specifies the sites, chemicals, and time period desired, fits an appropriate user-specified univariate model for each site and chemical selected, and the package produces a covariance matrix for use by MESP algorithms. © 2020, Springer Nature Switzerland AG.
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