管状模型中半参数bootstrap算法分析word格式论文.docxVIP

哈尔滨工业大学理学硕士学位论文 优秀毕业论文 - III - 精品参考文献资料 Abstract In this thesis we propose a new methodology to compute the critical values of using the Likelihood Ratio Test (LRT) on tubular models through Bootstrap simulation. We implement a Fast Double Bootstrap (FDB ） method to improve the reliability of critical values, and to evaluate the consistency of the Bootstrap, a triple-level Bootstrap simulation procedure is proposed and the direction selection technique is used to reduce the computational complexity in the Bootstrap algorithm. Firstly, we develop testing procedures for the tubular hypothesis. The LRT statistic L2 is proposed as the test statistic and an iterative algorithm of computation is developed. The limiting distribution of the LRT statistic is used to construct the asymptotic critical value of the LRT statistic. Secondly, we apply the tubular testing method to data in a two-way table when model is row-column independent. The testing index ?? ?????is compared with other goodness-of-fit statistics, The LRT statistics are calculated for tubes with different tolerance radius. A semiparametric Bootstrap method is used to simulate the distribution 2nL2 of the LRT statistic, then we compare the asymptotic distribution with the distribution obtained by Bootstrap simulation. We show how setting the critical value using Bootstrap testing results in rather substantial cha nges in ????inference in moderate sample sizes. We briefly discuss the possible reason for this difference. Lastly, we address whether the Bootstrap test achieves the right size reliably. This evaluation involves three levels of simulation. We develop an efficient procedure using direction selection and find that Bootstrap testing is satisfyingly accurate in size, and just a bit conservative. Keywords: Bootstrap, tubular model, likelihood ratio test, goodness of fit test 目 录 摘 要 I  HYPERLINK \l _bookmark0 Abstract II  HYPERLINK \l _b