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>