Path Integral Method for Estimation of Time Series

Posted in Science on July 21, 2008

Path Integral Method for Estimation of Time Series

Lecture content: 

  • Data Assimilation
  • Collaborators
  • Three Estimation Problems
  • Turning a model into a state estimation problem
  • Statement of the Problem
  • GOAL: estimate moments
  • A Nonlinear Example
  • Observations
  • Extended Kalman Filter
  • Alternative Approaches
  • Observations
  • KSP Filter Results
  • Why not KSP?
  • A Statistical-Mechanical Digression
  • Fact: log n! 1/4 n log n - n
  • Path Integral Method
  • Otherwise use sampling
  • Hybrid Monte Carlo
  • The HMC algorithm
  • What’s going on?
  • Unigrid Monte Carlo
  • Generalized HMC
  • PIMC Results
  • RESULTS: decorrelation time
  • Conclusions (Sampling)
  • Further Information

Author: Juan Restrepo, Mathematics Department, University of Arizona

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Tags: Science, Lectures, Computer Science, Data Mining, Machine Learning, VideoLectures.Net, Markov Processes, Time Series Analysis