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Bootstrap methods have been developed and extended in a large number of fields of statistics ever since the first inception by Efron(1979).This paper gives an introduction of the basic methodology,historical developments and some frontiers of the bootstrap theory.The main directions introduced in this paper includes: bootstrap for i.i.d data,model-based bootstrap,block bootstrap,sieve bootstrap,transform-based bootstrap,bootstrap for Markov process,bootstrap for long range dependence and bootstrap for spatial data,among which the first direction is the most fundamental,and other directions can be regarded as extensions under certain conditions.At the same time,we'll give some program scripts for different bootstrap algorithms;our tool is R language,which is being widely adopted nowadays in implementing new methods and models of statistics by international academicians.
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Basic Information:
China Classification Code:F224
Citation Information:
[1]XIE Yi-hui1,2,ZHU Yu1,3(1.School of Statistics,Renmin University of China,Beijing 100872, China,2.Center for Applied Statistics,Renmin University of China,Beijing 100872,China,3.School of Statistics,Xi'an University of Finance and Economics,Xi'an 710061,China).Bootstrap Methods:Developments and Frontiers[J].Journal of Statistics and Information,2008,No.89(02):90-96.
2008-02-10
2008-02-10