各位刷分的朋友,刷单词貌似是没有用的,回帖加分貌似和回帖的字数有关,我决定先实验一下,copy一点其他的东西进来,看看长文是不是能多加一点分,再来汇报结果。
While convergence properties of many sampling selection methods can be proven to hold in a
context of approximation of Feynman-Kac solutions using sequential Monte Carlo simulations, there is
one particular sampling selection method introduced by Baker (1987), closely related with “systematic
sampling” in statistics, that has been exclusively treated on an empirical basis. The main motivation
of the paper is to start to study formally its convergence properties, since in practice it is by far
the fastest selection method available. One will show that convergence results for the systematic
sampling selection method are related to properties of peculiar Markov chains.
While convergence properties of many sampling selection methods can be proven to hold in a
context of approximation of Feynman-Kac solutions using sequential Monte Carlo simulations, there is
one particular sampling selection method introduced by Baker (1987), closely related with “systematic
sampling” in statistics, that has been exclusively treated on an empirical basis. The main motivation
of the paper is to start to study formally its convergence properties, since in practice it is by far
the fastest selection method available. One will show that convergence results for the systematic
sampling selection method are related to properties of peculiar Markov chains.