• DocumentCode
    476186
  • Title

    The position and gap distribution in stochastic perch system and its application in a model of non-replacing sample

  • Author

    Li, Chun-lan ; Zhang, Yu-fen

  • Author_Institution
    Coll. of Sci., Hebei Agric. Univ., Baoding
  • Volume
    4
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    2402
  • Lastpage
    2406
  • Abstract
    This paper proposes a probability model of stochastic perch system. Picking randomly positions from N positions, the joint probability distribution and the marginal probability distribution of the positions and the gaps are obtained. Furthermore a probability model of sampling without replacement is discussed in this paper, and the conclusion is that the number of experiments in sampling without replacement has the same distribution as the positions in stochastic perch system. Compared with the replacing sample, the conclusion is, when the population is small, the difference between the distributions of sampling without and with replacement is big, but when the population is very large and when the ratio of n to N tend to a constant p, the limit distribution of the number of experiments in sampling without replacement is the same as the distribution of the number of experiments in sampling with replacement.
  • Keywords
    statistical distributions; stochastic systems; gap distribution; joint probability distribution; marginal probability distribution; nonreplacing sample; sampling distributions; stochastic perch system; Agriculture; Application software; Cybernetics; Educational institutions; Machine learning; Mathematical model; Mathematics; Probability distribution; Sampling methods; Stochastic systems; Negative binomial distribution; Negative hyper-geometric distribution; Sampling without replacement; Stochastic perch system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620808
  • Filename
    4620808