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

Techniques and Methods 7-C20
By: , , and 
https://doi.org/10.3133/tm7C20

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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
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
Publication Date April 28, 2020
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
Additional publication details