相依隨機序列滑動平均的強偏差定理的研究
[Abstract]:In the late 1970s, Professor Liu Wen and his collaborators extended the strong limit theorem of probability theory to the case of inequality, established the strong deviation theorem of random sequence, and obtained abundant research results. In this paper, based on the previous studies, we consider the strong deviation theorems for a class of dependent random sequences with respect to the moving average of different reference product distributions in the case of different reference product distributions. The basic idea of the study is to introduce the sliding likelihood ratio and sliding relative entropy as a random measure of the deviation between the joint distribution and the reference product distribution of dependent random sequences. By limiting the range of sliding relative entropy, a subset of the sample space is given, and the upper and lower bounds of the moving average of random sequences, that is, the strong deviation theorem, are obtained. The main point of the proof is to construct a sliding likelihood ratio with parameters. By using the classical Borel-Cantelli Lemma and the analysis method, we obtain almost everywhere convergence inequalities. The full text is divided into six chapters: the first chapter is the introduction part, which introduces the background of this paper and the basic ideas and methods of studying the strong deviation theorem of dependent random sequence; The second chapter briefly introduces the relevant basic theorems and concepts, as well as the research results related to this paper; In chapter 3, the concepts of sliding likelihood ratio and sliding relative entropy are introduced to study some strong deviation theorems for sliding average of random controlled random sequences. In chapter 4, we continue to study the strong deviation theorems of continuous sources relative to memoryless Gamma sources, and in chapter 5, we study a class of strong deviation theorems for the moving mean of random sequences with arbitrary dependent sequences and countable doubly nonhomogeneous Markov universal culverts. Chapter six summarizes and prospects the full text.
【學位授予單位】:安徽工業(yè)大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:O211.4
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