activity
20102023
most citedMonitoring procedure for parameter change in causal time series

20 citations · 38 across the 17 of their papers we have counts for

collaborators

19 papers

stat.ML2023

Sparse-penalized deep neural networks estimator under weak dependence

William Kengne, Modou Wade

We consider the nonparametric regression and the classification problems for -weakly dependent processes. This weak dependence structure is more general than conditions such as,…

math.ST2022

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…

math.ST2022

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…

math.ST2021

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($…

math.ST2021

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…

math.ST2021

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…