This site will look much better in a browser that supports web standards, but it is accessible to any browser or Internet device.

Welcome to David van Dyk's web site photo: dvd


  1. Kasyap, V. L., van Dyk, D. A., McKeough, K., Primini, F., Jerius, D, Gowrishankar, A., Siemiginowska, A., and Zezas, A. (2017). X-raying the Evolution of SN~1987a. In the Proceedings of the International Astronomical Union (Editors: M. Renaud, A. Marcowith, G. Dobner, A.~K. Ray, and A.~M. Bykov), No. 331, submitted. (Available on request.)

  2. Jiao, X. and van Dyk, D. A. and Trotta, R. and Shariff, H. (2016). The Efficiency of Next-Generation Gibbs-Type Samplers: An Illustration Using a Hierarchical Model in Cosmology. In the Proceedings of the 2014 ICSA/KISS Joint Applied Statistics Symposium in Portland, OR (Editors: Z. Jin, M. Liu, and X. Luo), 167-184. (DOI: 10.1007/978-3-319-42571-9). (Download pdf.)

  3. Stenning, D., van Dyk, D. A., Yu, Y., Kashyap, V. (2015). A Bayesian Analysis of the Solar Cycle Using Multiple Proxy Variables. In Current Trends in Bayesian Methodology with Applications (Editors: S. K. Upadhyay, U. Singh, D. K. Dey, and A. Loganathan), Chapman \ Hall/CRC Press, 585--608. (Download pdf.)

  4. Stenning, D., Kashyap, V., Lee, T. C. M., van Dyk, D. A., and Young, C. A. (2012). Morphological Image Analysis and Its Application to Sunspot Classification. In Statistical Challenges in Modern Astronomy V (Editors: G. J. Babu and E. D. Feigelson), Springer Verlag, New York, 329--342. (Download pdf.)

  5. van Dyk, D. A. (2011). Setting Limits, Computing Intervals, and Detection. In Proceedings of Phystat 2011 (Editors: H. Prosper and L. Lyons), CERN Yellow Report, 149-157. (Download pdf.)

  6. van Dyk, D. A. and Park, T. (2011). Partially Collapsed Gibbs Sampling & Path-Adaptive Metropolis-Hastings in High-Energy Astrophysics. In Handbook of Markov Chain Monte Carlo (Editors: S. Brooks, A. Gelman, G. Jones and X.-L. Meng), Chapman & Hall/CRC Press, 383-399. (Download pdf.)

  7. Connors, A. and van Dyk, D. A. (2007). How To Win With Non-Gaussian Data: Poisson Goodness-of-Fit. In Statistical Challenges in Modern Astronomy IV (Editors: G. J. Babu and E. D. Feigelson), Astronomical Society of the Pacific, San Francisco, Vol. CS371, 101-117. (Download pdf.)

  8. Glickman, M. E. and van Dyk, D. A. (2007). Basic Bayesian Methods. In Methods in Molecular Biology: Elementary Biostatistics (Editor: Walter T. Ambrosius), Humana Press, Totowa, New Jersey, 319-338. (Download pdf.)

  9. van Dyk, D. A. and Park, T., (2004). Efficient EM-Type Algorithms for Fitting Spectral Lines in High Energy Astrophysics. In Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives: An Essential Journey with Donald Rubin's Statistical Family (Editors: A. Gelman and X. L. Meng), Wiley \& Sons, New York, 285-296. (Download pdf.)

  10. van Dyk, D. A. (2004). Highly-Structured Statistical Models in High Energy Astrophysics. In Proceedings of the Conference on Statistical Problems in Particle Physics, Astrophysics, and Cosmology (Editors: L. Lyons, R. Mount, and R. Reitmeyer), SLAC Technical Publications Department, Menlo Park, CA, 114-121. (Download pdf.)

  11. van Dyk, D. A. (2003). Hierarchical Models, Data Augmentation, and Markov Chain Monte Carlo with discussion. In Statistical Challenges in Modern Astronomy III (Editors: G. J. Babu and E. D. Feigelson), Springer, New York, 41-56. (Download pdf.)

  12. van Dyk, D. A. and Hans, C. M. (2002). Accounting for Absorption Lines in Images Obtained with the Chandra X-ray Observatory. In Spatial Cluster Modelling (Editors: D. Denison and A. Lawson), CRC Press, London, 175-198. (Download pdf.)

  13. van Dyk, D. A. and Meng, X. L. (2000). The EM Algorithm. Invited entry in The Encyclopedia of Mathematics, Kluwer Academic Publishers, Dordrecht.