Empirical Process Techniques for Dependent Data - Tapa blanda

Sinopsis

Part I: A Tutorial on Empirical Process Techniques for Dependent Data * Part II: Techniques for the Empirical Process of Stationary Sequences * Weak Dependence: Models and Applications * Maximal Inequalities and Empirical Central Limit Theorems * On Hoeffding's Inequality for Dependent Random Variables * On the Coupling of Dependent Random Variables and Applications * Empirical Processes of Residuals * Part III: The Empirical Process of Long-Range Dependent Processes * Asymptotic Expansion of the Empirical Process of Long Memory Moving Averages * The Reduction Principle for the Empirical Process of a Long Memory Linear Process * Distributional Limit Theorems for Empirical Processes Generated by Functions of a Stationary Gaussian Process * Part IV: Empirical Spectral Process Techniques * Empirical Spectral Processes and Nonparametric Maximum Likelihood Estimation for Time Series * Empirical Processes Techniques for the Spectral Estimation of Fractional Processes * V: The Tail Empirical Process in Extreme Value Theory * Tail Empirical Processes Under Mixing Conditions * VI: Bootstrap Techniques * On the Bootstrap and Empirical Processes for Dependent Sequences * Frequency Domain Bootstrap for Time Series

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