Asymptotic results for empirical measures of weighted sums of independent random variables
BERCU, Bernard
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Laboratoire de Statistique et Probabilités [LSP]
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Laboratoire de Statistique et Probabilités [LSP]
BERCU, Bernard
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Laboratoire de Statistique et Probabilités [LSP]
< Leer menos
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Laboratoire de Statistique et Probabilités [LSP]
Idioma
en
Article de revue
Este ítem está publicado en
Electronic Communications in Probability. 2006, vol. 12, p. 184-199
Institute of Mathematical Statistics (IMS)
Resumen en inglés
We prove that if a rectangular matrix with uniformly small entries and approximately orthogonal rows is applied to the independent standardized random variables with uniformly bounded third moments, then the empirical CDF ...Leer más >
We prove that if a rectangular matrix with uniformly small entries and approximately orthogonal rows is applied to the independent standardized random variables with uniformly bounded third moments, then the empirical CDF of the resulting partial sums converges to the normal CDF with probability one. This implies almost sure convergence of empirical periodograms, almost sure convergence of spectra of circulant and reverse circulant matrices, and almost sure convergence of the CDF's generated from independent random variables by independent random orthogonal matrices. For special trigonometric matrices, the speed of the almost sure convergence is described by the normal approximation and by the large deviation principle.< Leer menos
Orígen
Importado de HalCentros de investigación