Cosma Shalizi is an assistant professor of statistics at Carnegie Mellon University, where his research focuses on aspects of the statistical analysis of complex systems: nonlinear prediction algorithms, heavy-tailed distributions, contagion in networks, and self-organizing processes. Previously, he was a post-dcotoral fellow at the University of Michigan’s Center for the Study of Complex Systems and at the Santa Fe °ËØÔ±¬ÁÏ, where he is now an external faculty member. He got is Ph.D. in theoretical physics from the University of Wisconsin-Madison in 2001.
Cosma Shalizi
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Time Series Forecasting: Model Evaluation and Selection Using Nonparametric Risk Bounds
We derive generalization error bounds — bounds on the expected inaccuracy of the predictions — for traditional time series forecasting models.
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Why Economics Needs Data Mining
Cosma Shalizi urges economists to stop doing what they are doing: Fitting large complex models to a small set of highly correlated time series data.