Decoupling theory provides a general framework for analyzing problems involving dependent random variables as if they were independent. It was born in the early eighties as a natural continuation of martingale theory and has acquired a life of its own due to vigorous development and wide applicability. The authors provide a friendly and systematic ...
This volume contains lectures on probability theory and statistics. They examine decoupling and limit theorems for U-statistics and U-processes, aspects theory of the bootstrap, percolation and disordered systems, and finite Markov Chains.
This work encompasses a wide range of topics in both statistics and probability theory, centering around the development and application of powerful methods in the areas of probability on Banach spaces, Gaussian process theory, and strong and distributional approximation.
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