Publications & Reports

• Technical Reports
• Published Research

Statistical Theory & Methodology

Department faculty and students work on many topics in statistical theory and methodology. Consult individual faculty web pages for descriptions of interest. Here are some major categories comprising the research done here at Carnegie Mellon:

• Algebraic statistics
• Bayesian inference
• Clustering
• Functional data analysis
• Graphical models
• High-dimensional statistics
• Optimization and algorithms
• Machine learning
• Network models
• Nonparametric methods
• Point processes
• Spectral methods and manifold learning
• State-space models
• Time series
• Foundations of inference
• Categorical data analysis
• Census and survey methodology
• History of statistics

Cross-disciplinary Research

Our Department of Statistics began in a Carnegie Mellon environment that stressed inter-disciplinary research. As a result we have established many long-term collaborations in a wide variety of areas. Select from the list below for a full description of each.

• Astrostatistics
• Bioinformatics
• Biostatistics
• Education, policy, and social sciences
• Neuroscience
• Privacy and cyber-security
• Law and justice