Title
Convergence of Dependent Random Variables: Central Limit Theorems, BerryEsseen Bounds, Martingalelike Sequences, Csequences, ,Used
Delivery time: 8-12 business days (International)
Central Limit Theorems, Rates of Convergence are derived for dependent random variables, with relaxed conditions on the dependence. Most of known mixing conditions like strong (alpha) mixing, absolute regular (betamixing),... will satisfy them. This new notion of measure of dependence is developed naturally from the classical Characteristic Function Method, less intuitive but may be more suitable in applications than mixing ones. As it is born from the wellknown tool for independent r.v.s's Limit Theorems. Theorems and examples given here prove this notion. Otherwise, it may reach the limit in process of defining measure of the dependence, as argued in this book. On the other aspect, almost sure convergence of adapted sequence, especially of Martingalelike one, is discussed. Csequence is created, showed not comparative with Amart, Martingaleinthelimit, by examples. It also is a natural extension of Martingale, derived by seeking condition ensuring a.s. convergence. Also, a phimixing Strong Law and some examples of Linear Process are given.
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This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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