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In this paper, we approach the variance changepoints detection problem from a multiple testing setting. After proving that the standard Step-Up and Step-Down procedures are inadmissible for the standa...
This note examines the influence of covariance inflation on the distance between the measured observation and the simulated (or predicted) observation with respect to the state estimate. In order for ...
Efficient particle filtering through residual nudging     Efficient  particle filtering  residual  nudging       font style='font-size:12px;'> 2013/5/2
We introduce an auxiliary technique, called residual nudging, to the particle filter to enhance its performance in cases that it performs poorly. The main idea of residual nudging is to monitor, and i...
Residual variance and the signal-to-noise ratio are important quantities in many statistical models and model fitting procedures. They play an important role in regression diagnostics, in determining ...
Residual Component Analysis     Residual Component  Analysis       font style='font-size:12px;'> 2011/7/6
Probabilistic principal component analysis (PPCA) seeks a low dimensional representation of a data set in the presence of independent spherical Gaussian noise, Sigma = (sigma^2)*I. The maximum likelih...
This paper uses the concept of characterized model for bivariate extensions of univariate life distributions based on mean residual life properties. Different bivariate distributions can be generated ...
On Weighted Residual and Past Entropies      Life distributions  entropy  residual lifetime  past lifetime       font style='font-size:12px;'> 2010/4/27
We consider a “length-biased” shift-dependent information measure, related to the differential entropy in which higher weight is assigned to large values of observed random variables. This allows us...

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