Abstract: Abrupt shifts in the level of a time series represent important information and should be preserved in statistical signal extraction. We investigate rules for detecting l...
Robustified rank tests, applying a robust scale estimator, are investigated for reliable and fast shift detection in time series. The tests show good power for sufficiently larg...
We present an algorithm for computing the probability density function of the product of two independent random variables, along with an implementation of the algorithm in a compu...
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
An efficient estimate for the change point in the hazard function is obtained. This is based on a Bayesian estimator which uses equations concerning the parameters of a recently ...