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

Hessa Al-Thani () and Jon Lee ()
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Hessa Al-Thani: University of Michigan
Jon Lee: University of Michigan

SN Operations Research Forum, 2020, vol. 1, issue 3, 1-21

Abstract: Abstract 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.

Keywords: Maximum-entropy sampling; Covariance matrix; Environmental monitoring; Environmetrics; NADP; NTN (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s43069-020-0011-z

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