in this paper, a bayesian approach is proposed for shift point detection in an inverse gaussian distribution. in this study, the mean parameter of inverse gaussian distribution is assumed to be constant and shift points in shape parameter is considered. first the posterior distribution of shape parameter is obtained. then the bayes estimators are derived under a class of priors and using variou...

One important parameter for an ultrasonic transducer is the echo it yields from a pointlike reflector. It can be measured directly but there are however certain problems connected with this. We propose an alternative method to calculate the echo from a pointlike reflector by measuring the echoes from sliding halfplanes. Using a tomographic way of reasoning, we can calculate the point echoes fro...

In the asymptotic setting of the change-point estimation problem the limiting behavior of Bayes procedures for a general loss function is studied. It is demonstrated that the distribution of the diierence between the Bayes estimator and the parameter converges to the distribution of a (nondegenerate) random variable. The sequence of minimum Bayes risks is shown to converge to its supremum, and ...

Change point detecting problem is an important task in data mining applications. Standard statistical procedures for change point detection, based on maximum likelihood estimators, are complex and require building of parametric models of data. Instead, the methods of computational statistics replace complex statistical procedures with an amount of computation; so these methods become more popul...

Let M be an m-dimensional smooth compact manifold embedded in R, where m is a constant known to us. Suppose that a dense set of points are sampled from M according to a Poisson process with an unknown parameter. Let p be any sample point, let % be the local feature size at p, and let %ε be the distance from p to the (n + 1)th nearest sample point for some n between ( m+1 2 ) + 1 and ( d+1 2 ) ....

A hidden Markov model is considered where the dynamics of the hidden process change at a random ‘change point’ . In principle this gives rise to a non-linear filter but closed form recursive estimates are obtained for the conditional distribution of the hidden process and of .

when a change occurs in a process, one expects to receive a signal from a control chart as quickly as possible. upon the receipt of signal from the control chart a search for identifying the source of disturbance begins. however, searching for assignable cause around the signal time, due to the fact that the disturbance may have manifested itself into the rocess sometimes back, may not always l...

Modeling the deformable shape of the left atrium is of strong interest for many applications in cardiac diagnosis and intervention. In this paper, we propose a method for left atrium shape modeling using non-rigid point cloud registration. In particular, we build upon the concept of Coherent Point Drift (CPD) registration that considers the alignment as a probability density estimation problem....