10.6084/m9.figshare.5102959.v2
Hang Qian
Hang
Qian
Inequality Constrained State-Space Models
Taylor & Francis Group
2017
Kalman filter
Particle filter
Rao-Blackwellization
Sequential Monte Carlo
2017-12-14 14:30:22
Journal contribution
https://tandf.figshare.com/articles/journal_contribution/Inequality_Constrained_State_Space_Models/5102959
<p>The standard Kalman filter cannot handle inequality constraints imposed on the state variables, as state truncation induces a nonlinear and non-Gaussian model. We propose a Rao-Blackwellized particle filter with the optimal importance function for forward filtering and the likelihood function evaluation. The particle filter effectively enforces the state constraints when the Kalman filter violates them. Monte Carlo experiments demonstrate excellent performance of the proposed particle filter with Rao-Blackwellization, in which the Gaussian linear sub-structure is exploited at both the cross-sectional and temporal levels.</p>