Weak convergence of stochastic processes

Auteurs

• Vidyadhar Mandrekar

Paramètres

• Mathématiques
• De Gruyter graduate

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The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion. Contents: Weak convergence of stochastic processes Weak convergence in metric spaces Weak convergence on C [0, 1] and D [0,∞) Central limit theorem for semi-martingales and applications Central limit theorems for dependent random variables Empirical process Bibliography

Achat du livre

• Année de publication: 2016
• Reliure: (rigide)