7 citations · 9 across the 10 of their papers we have counts for
14 papers · 1 filter
Statistical learning for -weakly dependent processes
Mamadou Lamine Diop, William Kengne
We consider statistical learning question for -weakly dependent processes, that unifies a large class of weak dependence conditions such as mixing, association, The cons…
Some asymptotic results for time series model selection
William Kengne
We consider the model selection problem for a large class of time series models, including, multivariate count processes, causal processes with exogenous covariates. A procedure ba…
Efficient and Consistent Data-Driven Model Selection for Time Series
Jean-Marc Bardet, Kamila Kare, William Kengne
This paper studies the model selection problem in a large class of causal time series models, which includes both the ARMA or AR() processes, as well as the GARCH or ARCH($…
Epidemic change-point detection in general causal time series
Mamadou Lamine Diop, William Kengne
We consider an epidemic change-point detection in a large class of causal time series models, including among other processes, AR(), ARCH(), TARCH(), ARMA-G…
A general procedure for change-point detection in multivariate time series
Mamadou Lamine Diop, William Kengne
We consider the change-point detection in multivariate continuous and integer valued time series. We propose a Wald-type statistic based on the estimator performed by a general con…
Epidemic change-point detection in general integer-valued time series
Mamadou Lamine Diop, William Kengne
In this paper, we consider the structural change in a class of discrete valued time series, which the true conditional distribution of the observations is assumed to be unknown. Th…