Professor Johnson's research interests focus on Markov chain Monte Carlo (MCMC) algorithms. Her goal is to develop a set of practical yet theoritically sound conditions under which it is possible for practitioners to determine the amount of simulation effort required to achieve prespecified levels of accuracy in the MCMC procedure. Johnson is currently a Ph.D. candidate in the School of Statistics at the University of Minnesota. In addition to her academic work, Johnson worked with the National Center for Infectious Diseases, Centers for Disease Control and Prevention in Fort Collins. EDUCATION: B.A., University of Wisconsin, 2001; M.A., Colorado State University, 2003 Johnson has been teaching at Macalester College since 2009.
Gibbs sampling for a Bayesian hierarchical general linear model (with Galin L. Jones), Electronic Journal of Statistics (2010)
Convergence rates of variable-at-a-time algorithms, The Thirteenth Meeting of New Researchers in Statistics and Probability (2010)