State space models on special manifolds

  • Authors:
  • Yasuko Chikuse

  • Affiliations:
  • Faculty of Engineering, Kagawa University, Takamatsu-shi, Kagawa-ken, Japan

  • Venue:
  • Journal of Multivariate Analysis
  • Year:
  • 2006

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Abstract

This paper concerns modeling time series observations in state space forms considered on the Stiefel and Grassmann manifolds. We develop a state space model relating the time series observations to a sequence of unobserved state or parameter matrices assuming the matrix Langevin noise processes on the Stiefel manifolds. We show a Bayes method for estimating the state matrices by the posterior modes. We consider a further extended state space model where two sequences of unobserved state matrices are involved. A simple state space model on the Grassmann manifolds with matrix Langevin noise processes is also investigated.