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• Journal Articles
• Edited Volumes
• Software
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SOFTWARE PUBLICATIONS:

1. pyBLoCXS: Bayesian Low Count X-ray Spectral analysis in Python. This package provides MCMC-based methods for high-energy spectral analysis within the CIAO/Sherpa software package.
   
   The code will soon be relased on the Astrostatistics page at the Harvard-Smithsonian Center for Astrophysics. (Download Software).
   
   
2. EMC2: Bayesian Multi-Scale Analysis of Low-Count Images. This package is designed for Multi-Scale Non-parametric Image analysis for use in High-Energy Astrophysics. The code implements an MCMC sampler that simultaneously fits the image and the necessary tuning/smoothing parameters in the model. The model-based approach allows for quantification of the standard error of the fitted image.
   
   The code is expected to be posted soon on Astrostatistics page at the Harvard-Smithsonian Center for Astrophysics. (Download Software). Two related papers are available. (Download related ApJ paper.). (Download related SCMA paper.).
   
   
3. BEHR: Bayesian Estimation of Hardness Ratios. This code uses Poisson models for principled Bayesian estimation of hardness ratios in ultra low-resolution spectral analysis for use in high-energy astrophysics.
   
   The computer code and a paper describing and illustrating the method are available. (Download Software). (Download related ApJ paper.).
   
   
4. MNP: R Package for Fitting the Multinomial Probit Model. This package used the method of marginal data augmentation to construct efficient MCMC samplers for the multinomial probit model.
   
   An R-package and two papers describing the method are available. (Download Software). (Download related JoE paper.). (Download related JSS paper.).