User Guide to Bayesian Modeling of Non-Stationary, Univariate, Spatial Data Using R-Language Package BMNUS

Techniques and Methods 7-C20
By: , and 

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Abstract

Bayesian modeling of non-stationary, univariate, spatial data is performed using the R-language package BMNUS. A unique advantage of this package is that it can map the mean, standard deviation, quantiles, and probability of exceeding a specified value. The package includes several R-language classes that prepare the data for the modeling, help select suitable model parameters, and help analyze the results. This user guide describes the BMNUS package and presents step-by-step instructions to model data that accompany the package.

Suggested Citation

Ellefsen, K.J, Goldman, M.A., and Van Gosen, B.S., 2020, User guide to the bayesian modeling of non-stationary, univariate, spatial data using R language package BMNUS: U.S. Geological Survey Techniques and Methods, book 7, chap. 20, 27 p., https://doi.org/10.3133/tm7C20.

ISSN: 2328-7055 (online)

Table of Contents

  • Abstract
  • Introduction
  • Preparatory Steps
  • Statistical Modeling
  • Data, Software, and Reproducibility
  • Acknowledgments
  • References Cited
  • Appendix 1. Estimate the Standard Deviation of the Measurement Error using Paired Measurements
  • Appendix 2. Reading and Writing Data for GIS Programs
  • Appendix 3. Cross validation using a validation dataset
  • Appendix 4. Troubleshooting Tips

Additional publication details

Publication type Report
Publication Subtype USGS Numbered Series
Title User guide to the bayesian modeling of non-stationary, univariate, spatial data using R language package BMNUS
Series title Techniques and Methods
Series number 7-C20
DOI 10.3133/tm7C20
Year Published 2020
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Crustal Geophysics and Geochemistry Science Center, Geology, Geophysics, and Geochemistry Science Center
Description Report: iv, 27 p.; 6 Companion Files
Online Only (Y/N) Y
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