Identification d'un processus autorégressif gaussien stable par la méthode de moyennisation logarithmique
type: Dataset
description: In the present work, we consider a stable one-dimensional gaussian autoregressive model in continous time. Using the limit theorems with logarithmic averaging obtained for continous local martingales, we construct then an estimator of the noise covariance $\sigma^{2}$ and an estimator of $\theta$ different of the one of the least squares estimator. By exploiting the weighting method we ameliorate the convergence rates of these new estimators.
issued: 2026-05-11T16:59:33.133581
language: fr
modified: 2026-05-11T16:59:33.133585
contact point: Organization
  fn: CCSD
keyword: almost-sure-central-limit-theorem
keyword: infoeu-reposemanticspreprint
keyword: law-of-iterated-logarithm
keyword: logarithmic-central-limit-theorem
keyword: martingale
keyword: mathmath-prmathematics-mathprobability-mathpr
keyword: preprints-working-papers-
keyword: weight
landing page: https://hal.science/hal-00079076

Identification d'un processus autorégressif gaussien stable par la méthode de moyennisation logarithmique
type: Distribution
format: HTML
issued: 2026-05-11T16:59:33.148051
modified: 2026-05-11T16:59:33.123754
access URL: https://hal.science/hal-00079076

test_moissonnage_selune
type: Agent