Weak Convergence of Stochastic Processes

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<p>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. </p> <p><strong>Contents:</strong><br>Weak convergence of stochastic processes<br>Weak convergence in metric spaces<br>Weak convergence on <em>C</em>[0, 1] and <em>D</em>[0,∞)<br>Central limit theorem for semi-martingales and applications<br>Central limit theorems for dependent random variables<br>Empirical process<br>Bibliography </p> <p></p>