## Asymptotic theory in probability and statistics with applicationsA collection of 18 papers, many of which are surveys, on asymptotic theory in probability and statistics, with applications to a wide variety of problems. This volume comprises three parts: limit theorems, statistics and applications, and mathematical finance and insurance. It is intended for graduate students in probability and statistics, and for researchers in related areas. |

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### Contents

Selfnormalized Limit Theorems | 3 |

Asymptotic Analysis of Random Partitions | 44 |

Limit Theorems on Adaptive Designs | 80 |

Copyright | |

15 other sections not shown

### Common terms and phrases

adaptive designs analysis applications approach approximation assume assumption asymptotic normality Bayesian Berry-Esseen bounds Brownian motion change point Chen Choquet integral classification computational condition constant convergence Corollary covariance Csorgo defined denote density function empirical likelihood error estimation finite GARCH Gaussian processes Gaussian random fields Gibbs sampler given implies independent inequality intersection iterated logarithm large deviation Lemma limit theorems limsup linear model linear regression log log Markov martingale Math Mathematics matrix maximum likelihood method MINQUE nonparametric obtained parameters partitions pixels Plancherel measure probability measure problem properties QTLs random variables random walks regression models rounded data satisfies Section self-intersection self-normalized sequence Shao spectral standard Stat stationary increments statistics stochastic sup inf SV models Theorem 3.1 theory tion treatment variance vector volatility Wang wavelet Wiener process Xiao Young diagram Zhang