Quality control charts aim at raising an alarm as soon as sequentially obtained observations
of an underlying random process no longer seem to be within stochastic fluctuations …

This paper studies single change-point detection in the volatility of a class of parametric
conditional heteroscedastic autoregressive nonlinear (CHARN) models. The conditional …

We consider the issue of strong consistency for model selection in a large class of causal
time series models, including AR (∞), ARCH (∞), TARCH (∞), ARMA–GARCH and many …

This study investigates a sequential procedure to detect changes in the parameter of ARMA-
GARCH models. Following the test procedure by Berkes et al.[Sequential change-point …

We study change-points tests based on U-statistics for absolutely regular observations. Our
method avoids some technical assumptions on the data and the kernel. The asymptotic …

We study a likelihood ratio test for detecting multiple weak changes in the mean of a class of
CHARN models. The locally asymptotically normal (LAN) structure of the family of …

In periods of dramatic stock price volatility, the identification of change points in stock price
time series is important for analyzing the structural changes in financial market data, as well …

We derive a Cramér–von Mises test for testing a class of time dependent coefficients
Coditional Heteroscedastic AutoRegressive Non Linear (CHARN) models. The test statistic …

We consider together the retrospective and the sequential change-point detection in a
general class of integer-valued time series. The conditional mean of the process depends …

We consider the sequential change-point detection in a general class of Poisson
autoregressive models. The conditional mean of the process depends on a parameter θ∗ …