1. V. Czellar, D. T. Frazier, E. Renault (2020). Approximate Maximum Likelihood for Complex Structural Models. Preprint.
  2. Z. M. Debaly, L. Truquet (2020). Iterations of dependent random maps and exogeneity in nonlinear dynamics. Arxiv-1908.00845.
  3. M. L. Diop, W. Kengne (2021). Epidemic change-point detection in general integer-valued time series. Arxiv-2103.13336.
  4. X. Milhaud, D. Pommeret, Y. Salhi, P. Vandekerkhove (2021). Shape constraint free two-sample contamination model testing. Hal-03201760.
  5. S. Nakakita, P. Alquier, M. Imaizumi (2022). Dimension-free Bounds for Sum of Dependent Matrices and Operators with Heavy-Tailed Distribution. Arxiv-2210.09756.

Preprints may be found on Arxiv and Hal.

  1. P. Doukhan, F. Roueff, J. Rynkiewicz (2020). Spectral estimation for non-linear long range dependent discrete time trawls. Electronic Journal of Statistics (14) 3157–3191. ISSN: 1935-7524. doi: 20-EJS1742.
  2. P. Alquier, K. Bertin, P. Doukhan, R. Garnier (2020). High-dimensional VAR with low-rank transition. Statistics and Computing 30, 1139–1153. doi: s11222-020-09929-7.
  3. A. Fernández-Fontelo, D. Moriña, A. Cabaña, A. Arratia, P. Puig (2020). Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case. PLoS ONE 15(12): e0242956. doi: journal.pone.0242956. Arxiv-2008.00262.
  4. N. Mamode Khan, H. Bakouch, A. D. Soobhug, M. G. Scotto (2020). Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach. Alexandria Engineering Journal. Pdf file. doi: j.aej.2020.12.047.
  5. W. Kengne (2020). Strongly consistent model selection for general causal time series. Statistics. DOI: j.spl.2020.109000.
  6. P. Doukhan, N. Mamode Khan, M. H. Neumann (2021). Mixing properties of integer-valued Skellam GARCH processes. ALEA, Lat. Am. J. Probab. Math. Stat. 18, 401–420. doi: 10.30757/ALEA.v18-18.
  7. B. Goncalves, T. Huillet (2021). A generating function approach to Markov chains undergoing binomial catastrophes. Journal of Statistical Mechanics: Theory and Experiments 033402 doi: 1742-5468/abdfcb., Arxiv-2101.03851.
  8. P. Doukhan, K. Fokianos, J. Rynkiewicz (2021). Mixtures of nonlinear Poisson autoregressions. doi: 10.1111/jtsa.12558. J. Time Ser. Anal. 42: 107–135. doi: 20-EJS1742.
  9. T. Huillet (2020). Statistics of Branched Populations Split into Different Types. Applications and Applied Mathematics, 15 (2) 764 – 800. ISSN: 1932-466.
  10. T. Huillet, S. Martinez (2021). Revisiting John Lamperti's maximal branching process, Stochastics, 94:2, 277-310 DOI: 10.1080/17442508.2021.1935949. Arxiv version.
  11. G. Pang, D. Alemayehu, V. de la Peña, M. J. Klass (2021). On the bias and variance of odds ratio, relative risk and false discovery proportion, Communications in Statistics - Theory and Methods. DOI: 03610926.2020.1867744.
  12. B. Goncalves, T. Huillet (2021). Keeping random walks safe from extinction and overpopulation in the presence of life-taking disasters. Mathematical Population Studies. doi: 08898480.2021.1976476.
  13. R. Garnier (2021). Modelisation of competition between time series. Arxiv-2009.14610. Annals of Operation Research.
  14. X. Milhaud, D. Pommeret, Y. Salhi, P. Vandekerkhove (2021). R-Project. admix: Package Admix for Admixture Models. Shape constraint free two-sample contamination model testing: hal-03201760 explanatory document.
  15. B. Goncalves, T. Huillet, E. Löcherbach (2021). On population growth with catastrophes. Arxiv-2007.03277. Stochastic Models (to appear).
  16. P. Doukhan, A. Leucht, M. H. Neumann (2022). Mixing properties of non-stationary INGARCH(1,1) processes. Arxiv-2011.05854v2. Bernoulli 28(1), 663-688. DOI: 10.3150/21-BEJ1362.
  17. P. Doukhan, J. Rynkiewicz, Y. Sahli (2022). Optimal Neighborhoods Selection for AR-ARCH Random Fields with Application to Mortality. Stats., Special Issue "Modern Time Series Analysis".
  18. B. Bobbia, P. Doukhan, X. Fan (2022). A Review on some weak dependence conditions. Hal-03325994. GJM (to appear).
  19. M. L. Diop, W. Kengne (2022). Inference and model selection in general causal time series with exogenous covariates. Electronic Journal of Statistics 16(1): 116-157.
  20. F. Maddanu, T. Proietti (2022) Modelling Persistent Cycles in Solar Activity. Solar Physics, 297-13. doi: 11207-021-01943.
  21. R. Garnier, R. Langhendries (2022). Concentration inequalities for non-causal random fields. Electronic Journal of Statistics 16(1): 1681-1725. DOI: 10.1214/22-EJS1992.
  22. T. Huillet (2022). Chance Mechanisms Involving SIBUYA Distributions and its relatives. Sankhya B: the Indian Journal of Statistics.
  23. K. Barigou, P.-O. Goffard, S. Loisel, Y. Salhi (2022). Bayesian model averaging for mortality forecasting using leave-future-out validation. Arxiv 2103.15434, available online 18 March, International Journal of Forecasting,
  24. Y. Jiao, Y. Salhi, S. Wang (2022). Dynamic Bivariate Mortality Modelling. Methodology and Computing in Applied Probability. DOI 10.1007/s11009-022-09955-0.
  25. T. Proietti, F., Maddanu (2022). Modelling cycles in climate series: The fractional sinusoidal waveform process. DOI j.jeconom.2022.04.008, Journal of Econometrics, ISSN 0304-4076.
  26. F. Maddanu (2022). Forecasting highly persistent time series with bounded spectrum processes. Statistical Papers. DOI s00362-022-01321-z
  27. P. Alquier, N. Marie, A. Rosier (2022). Tight risk bound for high dimensional time series completion. Electron. J. Statist. 16(1): 3001-3035. DOI: 10.1214/22-EJS2015.
  28. V. de la Pena, P. Doukhan, Y. Sahli (2022). A Dynamic Taylor's Law. Journal of Applied Probability, 59-2 , pp. 584 - 607, DOI: 10.1017/jpr.2021.40.
  29. B. Goncalves, T. Huillet, E. Löcherbach (2022). On decay-surge population models. Advances in Applied Probability (to appear).
  30. P. Alquier (2022). User-friendly introduction to PAC-Bayes bounds, in Approximate Bayesian Inference DOI: 10.3390/books978-3-0365-3790-0. This publication is a collaborative work and it does not mention ECODEP.
  31. J. M. Bardet, P. Doukhan, O. Wintenberger (2022). Contrast estimation of time-varying infinite memory processes. Arxiv-2005.07397, Stochastic Processes and their Applications, DOI:
  32. J. Cohen, T. Huillet (2022). Taylor's Law for some infinitely divisible probabbility distributions from population models. Journal of Statistical Physics. (to appear).
  33. X. Fan, P. Alquier, P. Doukhan (2022). Deviation inequalities for stochastic approximation by averaging. Stochastic Processes and their applications, DOI:
  34. H. Cherrat, J.-L. Prigent (2022). On the Hedging of Interest Rate Margins on Bank Demand Deposits. Computational Economics, DOI: 10.1007/s10614-022-10287-x.
  35. P. Doukhan, X. Fan, Z.-Q. Gao (2023). Cramér moderate deviations for a supercritical Galton-Watson process. Arxiv-2109.12374, Statistics and Probability Letters, Volume 192, January 2023. Doi: j.spl.2022.109711.
  36. P. Doukhan, M. H. Neumann, L. Truquet (2023). Stationarity and ergodic properties for some observation-driven models in random environments. Arxiv-2007.07623.

Springer Ecodep Volume
A special volume will be submitted to Springer.
Interested contributors may send submission proposals.
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In order to be included in the current page, please mention:
This work was funded by CY Initiative of Excellence
(grant "Investissements d'Avenir" ANR-16-IDEX-0008),
Project "EcoDep" PSI-AAP2020-0000000013.