geoBayes: The 'geoBayes' package

In geoBayes: Analysis of Geostatistical Data using Bayes and Empirical Bayes Methods

The geoBayes package

Description

Analysis of geostatistical data using Bayes and Empirical Bayes methods.

Details

This package provides functions to fit geostatistical data. The data can be continuous, binary or count data and the models implemented are flexible. Conjugate priors are assumed on some parameters while inference on the other parameters can be done through a full Bayesian analysis of by empirical Bayes methods.

Some demonstration examples are provided. Type demo(package = "geoBayes") to examine them.

Author(s)

Evangelos Evangelou <[e-mail]> and Vivekananda Roy <[e-mail]>

References

Roy, V., Evangelou, E. and Zhu, Z. (2014). Empirical Bayes methods for the transformed Gaussian random fields model with additive measurement errors. In Upadhyay, S. K., Singh, U., Dey, D. K., and Loganathan, A., editors, Current Trends in Bayesian Methodology with Applications, Boca Raton, FL, USA, CRC Press.

Roy, V., Evangelou, E., and Zhu, Z. (2015). Efficient estimation and prediction for the Bayesian spatial generalized linear mixed model with flexible link functions. Biometrics, 72(1), 289-298.

Evangelou, E., & Roy, V. (2019). Estimation and prediction for spatial generalized linear mixed models with parametric links via reparameterized importance sampling. Spatial Statistics, 29, 289-315.

Roy, V., & Evangelou, E. (2022). Selection of proposal distributions for multiple importance sampling. Statistica Sinica.

Examples

## Not run: 
demo(package = "geoBayes")
demo(rhizoctonia1, package = "geoBayes")
demo(rhizoctonia1, package = "geoBayes")

## End(Not run)

geoBayes documentation built on Aug. 21, 2023, 9:08 a.m.