Bruce G. Lindsay

Distinguished Professor of Statistics
Ph.D.: University of Washington, 1978
Dr. Bruce Lindsay's Home Page

Dr. Lindsay's research is in the following four areas.

  1. Nuisance parameters: When building a statistical model for data collected on a sample of individuals, it is typically necessary to include many parameters to make sure the model is rich enough to approximate the true state of nature. However, the standard methods of statistical analyses have major deficiencies when viewed in this framework. Dr. Lindsay has developed a theory for measuring the deficiency and methods free from the deficiency.
  2. Mixture models: If the heights of college students in a classroom are sampled, then the distribution of the heights will be nonnormal, and possibly bimodal, because the students are a mixture of males and females. Dr. Lindsay has developed a better set of tools for the analysis of data from such a population.
  3. Computer algorithms: There has been an explosion of new ideas and methods in statistics because the computer has made it feasible to be much more sophisticated and realistic in creating models. Dr. Lindsay's work includes designing computer programs, guaranteed to converge to the right answer, and on methods for constructing good initial estimates at which to start the program.
  4. Minimum distance and robustness: A long-standing concern in statistical methods has been the sensitivity of the answers to one or more incorrect data points; a robust method is one lacking this deficiency. Dr. Lindsay has been exploring a set of methods called minimum distance and has found a key to understanding their robustness properties.
Dr. Lindsay was a Woodrow Wilson Fellow (1969), a NATO Postdoctoral Fellow at Imperial College (1977), and received the Humboldt Senior Scientist Award (1991) in Berlin. He is a Fellow of the Institute of Mathematical Statistics.

 Representative Publications:

 Lindsay, B. G., and D. Boehning, and P. Schlattman. 1992. Computer Assisted Analysis of Mixtures (C.A. Man): Statistical Algorithms. Biometrics, 48:283-304.

 Lindsay, B. G., and K. Roeder. 1992. Residual diagnostics in the mixture model. Journal of the American Statistical Association, 87:785-795.

 Lindsay, B. G., J. Lynch, and H.-L. Hsi. 1992. On mixtures of hazards: Non-parametric maximum likelihood in a competing risk model. Non Parametric Statistics 2:89-103.