This is an archive of code related to a subset of my papers.

A system for programming with BUGS models (R)

NIMBLE is a R package for using a variety of algorithms with hierarchical statistical models. Please see the NIMBLE webpage. July 2014.

Distributed Gaussian process (bigGP) package (R)

The bigGP package is available on CRAN. bigGP distributes Gaussian process calculations across nodes in a distributed memory setting, using Rmpi. The class provides high-level methods for maximum likelihood with normal data, prediction, calculation of uncertainty (i.e., posterior covariance calculations), and simulation of realizations. In addition, bigGP provides an API for basic matrix calculations with distributed covariance matrices, including Cholesky decomposition, back/forwardsolve, crossproduct, and matrix multiplication. An arXiv preprint of our submission to Journal of Statistical Software that describes the approach and the software implementation can be obtained here. July 2013.

Code for analyses of using MRF models on a fine grid for modeling point and areal data (R)

The code in this archive carries out all of the analyses in my paper in Electronic Journal of Statistics on using MRF models on a fine grid for modeling point and areal data. April 2013.

Code for simulations on bias and precision of spatial regression estimators (R)

This code runs the simulations reported in my paper in Statistical Science on bias and precision of spatial regression estimators, which focuses on spatial confounding. May 2010.

Code for spatio-temporal modeling of PM (R)

This code fits the simple, yet effective, spatio-temporal models for predicting monthly PM10 and PM2.5 in the northeastern U.S., discussed in our paper in the Annals of Applied Statistics. The code fits a spatio-temporal model, with smooth covariate terms, in two stages, a first stage for monthly-varying terms and a second stage for time-invariant terms. Each stage contains both covariates and a spatial term (one spatial term for each month in the first-stage model. The code works directly (and hopefully seemlessly) with these data, used in our paper. August 2008.

Spectral Gaussian process (spectralGP) package (R)

The spectralGP package is available on CRAN. The code allows one to specify a Gaussian process as a linear combination of spectral basis functions. One can quickly simulate 1- and 2-d Gaussian processes as well as use the code in a Bayesian MCMC fitting procedure. See my associated article, published in Journal of Statistical Software, on using this library in the context of Bayesian modeling of spatial processes. This work builds on Chris Wikle's initial work on the spectral basis.

MCMC code for fitting Gaussian processes using the Fourier basis (R)

This template code allows one to fit models using the Fourier basis representation of Gaussian processes with various parameterizations and sampling schemes, following the development in my article, published in Journal of Statistical Software.

Spatial binary regression code (R)

I have code for fitting logistic regression models with a smooth spatial surface as part of the linear predictor. Also, I have a rough template for a MRF model based on the approach (and code) of H. Rue. This code accompanies my paper on fitting spatial models for binary outcomes. The methods included in the code file are a simple implementation of the gam() function in Simon Wood's mgcv library, a simple implementation of the PQL approach with geoadditive model style basis functions using Matt Wand's spm library, a Bayesian implementation of generalized geoadditive models and a Bayesian implementation of the spectral (Fourier) basis approach.

False Discovery Rate code (R/Splus and Matlab/octave)

For an overview, see the README file.

This zip file contains R code (it also works in Splus) and help files for applying the False Discovery Rate (FDR) methodology to determining significance using multiple p-values. A text file with just the code is also available. To use the code, source the file ('source fdr.R') and then use the function called 'fdr'.

For a Matlab version, download this .m file. This code also works in octave, an open source version of the Matlab language, but you need all 5 functions in their own individual .m files, so after downloading the file, manually create individual function files from the fdr.m file.

Additional details are available in our article, in Journal of Climate.

Thesis code (C++)

I do have C++ code for fitting the models in my dissertation, though this is not user-friendly and not designed for public use.

Last updated: June 2013.