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A Markov Chain Perspective on Adaptive Monte Carlo Algorithms
Markov Chain Perspective Adaptive Monte Carlo Algorithms
2015/7/8
This paper discusses some connections between adaptive Monte Carlo algorithms and general state space Markov chains. Adaptive algorithms are iterative methods in which previously generated samples are...
Decision Based Uncertainty Propagation Using Adaptive Gaussian Mixtures
Adaptive Gaussian Sum Decision Making
2011/7/19
Given a decision process based on the approximate probability density function returned by a data assimilation algorithm, an interaction level between the decision making level and the data assimilati...
Sequential estimation for covariate-adjusted response-adaptive designs
Covariate-adjustment logistic regression response-adaptive design se-quential estimation
2011/7/6
In clinical trials, a covariate-adjusted response-adaptive (CARA) design allows a subject newly entering a trial a better chance of being allocated to a superior treatment regimen based on cumulative ...
Modern Sequential Analysis and its Applications to Computerized Adaptive Testing
sequential analysis computerized adaptive testing mastery testing
2011/7/5
After a brief review of recent advances in sequential analysis involving sequential generalized likelihood ratio tests, we discuss their use in psychometric testing and extend the asymptotic optimalit...
On the efficiency of adaptive MCMC algorithms
MCMC process asymptotic properties MCMC algorithms
2009/3/30
We study a class of adaptive Markov Chain Monte Carlo (MCMC) processes which aim at behaving as an ``optimal'' target process via a learning procedure. We show, under appropriate conditions, that the ...