In many applied problems in the context of pattern recognition, the data often involve highly asymmetric observations. Normal mixture models tend to overfit when additional compone...
We consider multivariate density estimation with identically distributed observations. We study a density estimator which is a convex combination of functions in a dictionary and ...
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
This paper employs general multivariate normal distribution to develop a new efficient statistical timing analysis methodology. The paper presents the theoretical framework of the...
The paper reconsiders the autoregressive aided periodogram bootstrap (AAPB) which has been suggested in Kreiß and Paparoditis (2003). Their idea was to combine a time domain param...