## 6 Citations

Efficient and Consistent Data-Driven Model Selection for Time Series

- Mathematics, Computer Science
- 2021

This paper proves that consistent model selection criteria outperform classical AIC criterion in terms of efficiency and derives from a Bayesian approach the usual BIC criterion, by keeping all the second order terms of the Laplace approximation, a data-driven criterion denoted KC’.

General Hannan and Quinn criterion for common time series

- MathematicsStatistics
- 2022

This paper aims to study data driven model selection criteria for a large class of time series, which includes ARMA or AR(∞) processes, as well as GARCH or ARCH(∞), APARCH and many others processes.…

Some asymptotic results for time series model selection

- Mathematics, Computer Science
- 2022

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 based on a general…

Epidemic change-point detection in general causal time series

- MathematicsStatistics & Probability Letters
- 2022

Inference and model selection in general causal time series with exogenous covariates

- MathematicsElectronic Journal of Statistics
- 2022

In this paper, we study a general class of causal processes with exogenous covariates, including many classical processes such as the ARMA-GARCH, APARCH, ARMAX, GARCH-X and APARCH-X processes. Under…

## References

SHOWING 1-10 OF 19 REFERENCES

Testing for Parameter Constancy in General Causal Time‐Series Models

- Mathematics
- 2012

We consider a process belonging to a large class of causal models including AR(∞), ARCH(∞), TARCH(∞),… processes. We assume that the model depends on a parameter and consider the problem of testing…

Multiple breaks detection in general causal time series using penalized quasi-likelihood

- Mathematics
- 2012

This paper is devoted to the off-line multiple breaks detection for a general class of models. The observations are supposed to fit a parametric causal process (such as classical models AR(∞),…

Monitoring procedure for parameter change in causal time series

- MathematicsJ. Multivar. Anal.
- 2014

Model identification using the Efficient Determination Criterion

- Mathematics, Computer ScienceJ. Multivar. Anal.
- 2016

On model selection from a finite family of possibly misspecified time series models

- Computer ScienceThe Annals of Statistics
- 2019

A misspecification-resistant information criterion (MRIC) is proposed and it is shown that MRIC can be used in conjunction with a high-dimensional model selection method to select the (asymptotically) best predictive model across several high- dimensional misspecified time series models.

Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of affine causal processes

- Mathematics
- 2016

We prove the consistency and asymptotic normality of the Laplacian Quasi-Maximum Likelihood Estimator (QMLE) for a general class of causal time series including ARMA, AR($\infty$), GARCH,…

ASYMPTOTIC NORMALITY OF THE QUASI MAXIMUM LIKELIHOOD ESTIMATOR FOR MULTIDIMENSIONAL CAUSAL PROCESSES

- Mathematics
- 2007

Strong consistency and asymptotic normality of the Quasi-Maximum Likelihood Estimator (QMLE) are given for a general class of multidimensional causal processes. For particular cases already studied…

Model Selection Techniques: An Overview

- Computer ScienceIEEE Signal Processing Magazine
- 2018

An integrated and practically relevant discussions on theoretical properties of state-of-the-art model selection approaches are provided, in terms of their motivation, large sample performance, and applicability.

The Estimation of the Order of an ARMA Process

- Mathematics
- 1980

>2LK(j)E(n -j), Y,0?K(j)zi = k(z) = gh, where the K(j) decrease to zero at a geometric rate, and that the E(n) are the linear innovations. It has been assumed that &{x(n)} = 0 but this is immaterial…