State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering
(2018) Econometrics — Vol. 6, n° 4, p. 48 (2018)
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- Authors
Yang, Yukai 
Bauwens, Luc
- Abstract
- We develop novel multivariate state-space models wherein the latent states evolve on the Stiefel manifold and follow a conditional matrix Langevin distribution. The latent states correspond to time-varying reduced rank parameter matrices, like the loadings in dynamic factor models and the parameters of cointegrating relations in vector error-correction models. The corresponding nonlinear filtering algorithms are developed and evaluated by means of simulation experiments.
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Citations
Yang, Y., & Bauwens, L. (2018). State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering. Econometrics, 6(4), 48. https://doi.org/10.3390/econometrics6040048 (Original work published 2018)