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We present methods for online linear optimization that take advantage of benign (as opposed to worst-case) sequences. Specically if the sequence encountered by the learner is described well by a know...
Nonparametric deconvolution problem for dependent sequences
long range dependence linear processes error-in-variables models deconvolution
2009/9/16
We consider the nonparametric estimation of the density function of weakly and strongly dependent processes with noisy observations. We show that in the ordinary smooth case the optimal bandwidth choi...
Construction of weakly CUD sequences for MCMC sampling
completely uniformly distributed Gibbs sampler equidistribution probit quasi-Monte Carlo
2009/9/16
In Markov chain Monte Carlo (MCMC) sampling considerable thought goes into constructing random transitions. But those transitions are almost always driven by a simulated IID sequence. Recently it has ...