随机过程导出的测度列的近邻完全分离与变差收敛

ON CONTIGUITY, ENTIRE SEPARATION AND CONVERGENCE IN VARIATION OF SEQUENCES OF MEASURES INDURESINDUCED BY STOCHASTIC RROCESSES

  • 摘要: 本文利用测度的Kakutani距离证明了由正态过程及随机连续的独立增量过程导出的测度列的近邻、完全分离与变差收敛的充要条件,完善了原有的结论,或提供了简单而直接的证明方法。

     

    Abstract: By using the necessary and sufficient conditions for entire separation and convergence in variation of sequences of probability measures given in terms of Kakutani’s distance between probability measures, with respect to probability measures sequences induced by Gaussian processes and stochastically continuous processes with independent increments the necessary and sufficient conditions for the contiguty, entire separation and convergence in variation are shown.The conclusions about Gaussian processes are more complete than that in 4.With respect to processes with independent increments our calculations of Kakutani’s distance are simpler than that in 8, because we use the explicit forms of derivatives of measures induced by processes with independent increments.

     

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