Description Details Author(s) References See Also Examples

Analysis of geostatistical data using Bayes and Empirical Bayes methods.

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.

Evangelos Evangelou <e.evangelou@maths.bath.ac.uk> and Vivekananda Roy <vroy@iastate.edu>

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*.
http://dx.doi.org/10.1111/biom.12371

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