36-740 Advanced Methods I- Data over Space and Time

6 units, Carnegie Mellon University

A survey of methods for spatial, temporal and spatio-temporal statistics, with an emphasis on tools which can be applied in all three domains: Optimal linear prediction / estimation / de-noising ("Wiener filter", "kriging"); covariance function estimation, including low-rank approximations ("factor models"); state-space modeling and state estimation ("Kalman filter", "particle filter"); generative models and point processes; resampling methods for bootstrapping.

Prerequisites: none listed

Offered: Fall 2026

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