The method of permutation is introduced for the block re, sampling of moving block bootstrap, and is compard with the fixed block bootstrap and stationary bootstrap. Simulations are proformed, which verify that the bl...The method of permutation is introduced for the block re, sampling of moving block bootstrap, and is compard with the fixed block bootstrap and stationary bootstrap. Simulations are proformed, which verify that the block resampling of moving block bootstrap with permutation can effectively eliminete the number of abnormal data in the resampled data set and reduce the resampling errors of estimation.展开更多
The bootstrap method is one of the new ways of studying statistical math which this article uses but is a major tool for studying and evaluating the values of parameters in probability distribution.Our research is con...The bootstrap method is one of the new ways of studying statistical math which this article uses but is a major tool for studying and evaluating the values of parameters in probability distribution.Our research is concerned overview of the theory of infinite distribution functions.The tool to deal with the problems raised in the paper is the mathematical methods of random analysis(theory of random process and multivariate statistics).In this article,we introduce the new function to find out the bias and standard error with jackknife method for Generalized Extreme Value distributions.展开更多
This paper introduced a bootstrap method called truncated geometric bootstrap method for time series stationary process. We estimate the parameters of a geometric distribution which has been truncated as a probability...This paper introduced a bootstrap method called truncated geometric bootstrap method for time series stationary process. We estimate the parameters of a geometric distribution which has been truncated as a probability model for the bootstrap algorithm. This probability model was used in resampling blocks of random length, where the length of each blocks has a truncated geometric distribution. The method was able to determine the block sizes b and probability p attached to its random selections. The mean and variance were estimated for the truncated geometric distribution and the bootstrap algorithm developed based on the proposed probability model.展开更多
文摘The method of permutation is introduced for the block re, sampling of moving block bootstrap, and is compard with the fixed block bootstrap and stationary bootstrap. Simulations are proformed, which verify that the block resampling of moving block bootstrap with permutation can effectively eliminete the number of abnormal data in the resampled data set and reduce the resampling errors of estimation.
文摘The bootstrap method is one of the new ways of studying statistical math which this article uses but is a major tool for studying and evaluating the values of parameters in probability distribution.Our research is concerned overview of the theory of infinite distribution functions.The tool to deal with the problems raised in the paper is the mathematical methods of random analysis(theory of random process and multivariate statistics).In this article,we introduce the new function to find out the bias and standard error with jackknife method for Generalized Extreme Value distributions.
文摘This paper introduced a bootstrap method called truncated geometric bootstrap method for time series stationary process. We estimate the parameters of a geometric distribution which has been truncated as a probability model for the bootstrap algorithm. This probability model was used in resampling blocks of random length, where the length of each blocks has a truncated geometric distribution. The method was able to determine the block sizes b and probability p attached to its random selections. The mean and variance were estimated for the truncated geometric distribution and the bootstrap algorithm developed based on the proposed probability model.
