On the Almost Sure Central Limit Theorem for Vector Martingales: Convergence of Moments and Statistical Applications
BERCU, Bernard
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
BERCU, Bernard
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
< Leer menos
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Idioma
en
Rapport
Este ítem está publicado en
2008p. 26
Resumen en inglés
We investigate the almost sure asymptotic properties of vector martingale transforms. Assuming some appropriate regularity conditions both on the increasing process and on the moments of the martingale, we prove that ...Leer más >
We investigate the almost sure asymptotic properties of vector martingale transforms. Assuming some appropriate regularity conditions both on the increasing process and on the moments of the martingale, we prove that normalized moments of any even order converge in the almost sure cental limit theorem for martingales. A conjecture about almost sure upper bounds under wider hypotheses is formulated. The theoretical results are supported by examples borrowed from statistical applications, including linear autoregressive models and branching processes with immigration, for which new asymptotic properties are established on estimation and prediction errors.< Leer menos
Palabras clave en inglés
Almost sure central limit theorem
vector martingale
moment
stochastic regression
Orígen
Importado de HalCentros de investigación