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Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Dynamic Clustering Asymptotics Dependent Dirichlet Process Mixture
2013/6/17
This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The alg...
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Ergodic convergence Markov Chain Monte Carlo Metropolis-within Gibbs composite sampling Multivariatet mixtures Simulated annealing Variational Approx-imation
2013/6/14
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...
Power of Change-Point Tests for Long-Range Dependent Data
Change-point problems nonparametric change-point tests Wilcoxon two-sample rank test power of test local alternatives asymptotic relativeefficiency of tests long-range dependent data,long memory functional limit theorem
2013/4/28
We investigate the power of the CUSUM test and the Wilcoxon change-point test for a shift in the mean of a process with long-range dependent noise. We derive analytiv formulas for the power of these t...
A new method for obtaining sharp compound Poisson approximation error estimates for sums of locally dependent random variables
compound Poisson approximation coupling inequality law of small numbers
2010/10/19
Let $X_1,X_2,...,X_n$ be a sequence of independent or locally dependent random variables taking values in $\mathbb{Z}_+$. In this paper, we derive sharp bounds, via a new probabilistic method, for the...