ITERATIONS OF DEPENDENT RANDOM MAPS AND EXOGENEITY IN NONLINEAR DYNAMICS

Autor: Lionel Truquet, Zinsou Max Debaly

Publikováno v: Econometric Theory. 37:1135-1172

We discuss the existence and uniqueness of stationary and ergodic nonlinear autoregressive processes when exogenous regressors are incorporated into the dynamic. To this end, we consider the convergence of the backward iterations of dependent random

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::653d344c8214cf4a4b138bf5bab8cbf9
https://doi.org/10.1017/s0266466620000559

Root-$n$ consistent estimation of the marginal density in semiparametric autoregressive time series models

Autor: Lionel Truquet

Publikováno v: Bernoulli 25, no. 3 (2019), 2107-2136

In this paper, we consider the problem of estimating the marginal density in some autoregressive time series models for which the conditional mean and variance have a parametric specification. Under some regularity conditions, we show that a kernel t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::245621d98eecd5ed4b87a17dee04fc29
https://projecteuclid.org/euclid.bj/1560326439

Parameter Stability and Semiparametric Inference in Time Varying Auto-Regressive Conditional Heteroscedasticity Models

Autor: Lionel Truquet

Publikováno v: Journal of the Royal Statistical Society: Series B
Journal of the Royal Statistical Society: Series B, 2017, 79 (5), pp.1391-1414. ⟨10.1111/rssb.12221⟩
Journal of the Royal Statistical Society: Series B (Statistical Methodology)
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2017, 〈10.1111/rssb.12221〉
Journal of the Royal Statistical Society: Series B, Royal Statistical Society, 2017, 79 (5), pp.1391-1414. ⟨10.1111/rssb.12221⟩

Summary We develop a complete methodology for detecting time varying or non-time-varying parameters in auto-regressive conditional heteroscedasticity (ARCH) processes. For this, we estimate and test various semiparametric versions of time varying ARC

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b7acf93ec725f23a0ad23ab674bb2c2
https://doi.org/10.1111/rssb.12221

Nonparametric tests for Cox processes

Autor: Gaspar Massiot, Lionel Truquet, Benoît Cadre

Publikováno v: Journal of Statistical Planning and Inference
Journal of Statistical Planning and Inference, Elsevier, 2017, 184, pp.48-61. 〈10.1016/j.jspi.2016.12.001〉
Journal of Statistical Planning and Inference, Elsevier, 2017, 184, pp.48-61. ⟨10.1016/j.jspi.2016.12.001⟩
Journal of Statistical Planning and Inference, 2017, 184, pp.48-61. ⟨10.1016/j.jspi.2016.12.001⟩

International audience; In a functional setting, we elaborate and study two test statistics to highlight the Poisson nature of a Cox process when n copies of the process are available. Our approach involves a comparison of the empirical mean and the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed84f42ba818e184576cd32a9c699b97
https://hal.archives-ouvertes.fr/hal-01430572

A p-Order signed integer-valued autoregressive (SINAR(p)) model

Autor: Maher Kachour, Lionel Truquet

Publikováno v: Journal of Time Series Analysis. 32:223-236

In this article, we propose an extension of integer-valued autoregressive INAR models. Using a signed version of the thinning operator, we define a larger class of -valued processes, called SINAR, which can have positive as well as negative correlati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9a10b24f687123a5ed976185393a53b9
https://doi.org/10.1111/j.1467-9892.2010.00694.x