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Construction of Bayesian Deformable Models via Stochastic Approximation Algorithm：A Convergence Study
stochastic approximation algorithms non rigid-deformable templates shapes statistics Bayesian modeling MAP estimation
2010/4/29
The problem of the definition and the estimation of generative models based on deformable templates from raw data is of particular importance for modeling non-aligned data affected by various types of...
Posterior Convergence and Model Estimation in Bayesian Change-point Problems
change-point problems posterior distribution rate of convergence
2010/4/30
We study the posterior distribution of the Bayesian multiple change-point regression
problem when the number and the locations of the change-points are unknown. While it is
relatively easy to apply ...
We consider estimation procedures which are recursive in the sense
that each successive estimator is obtained from the previous one by a
simple adjustment. We propose a wide class of recursive estim...
Rate of Convergence in Recursive Parameter Estimation procedures
recursive estimation estimating equations stochastic approximation
2010/4/29
We consider estimation procedures which are recursive in the sense
that each successive estimator is obtained from the previous one by a
simple adjustment. We study rate of convergence of recursive ...
Recursive estimation of possibly misspecified MA(1) models：Convergence of a general algorithm
time series Robbins-Monro PLR AML RML1 RML2 misspecified models
2010/4/27
We introduce a recursive algorithm of conveniently general form
for estimating the coefficient of a moving average model of order one and
obtain convergence results for both correct and misspecified...
On rates of convergence for posterior distributions under misspecification
α-covering Bayesian nonparametrics Prior misspecification
2010/4/26
We extend the approach of Walker (2003, 2004) to the case of misspecified models.
A sufficient condition for establishing rates of convergence is given based on a key
identity involving martingales,...