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On the Stationary Distribution of Iterative Imputations
Multiple imputation Markov chain Monte Carlo
2011/1/21
Iterative imputation, in which variables are imputed one at a time each given a model predicting from all the others, is a popular technique that can be convenient and exible, as it replaces a potenti...
Iterative imputation, in which variables are imputed one at a time each given a model predicting from all the others, is a popular technique that can be convenient and flexible, as it replaces a poten...
Markov processes with product-form stationary distribution
Markov process stationary distribution
2009/3/23
We consider a continuous time Markov process (X,L), where X jumps between a finite number of states and L is a piecewise linear process with state space Rd. The process L represents an “inert drift” o...
Kalman Filtering with Intermittent Observations：Weak Convergence to a Stationary Distribution
Kalman Filtering Intermittent Observations Weak Convergence Stationary Distribution
2010/3/19
The paper studies the asymptotic behavior of Random Algebraic Riccati Equations (RARE) arising
in Kalman filtering when the arrival of the observations is described by a Bernoulli i.i.d. process. We ...