On the distribution of the leading statistics for the bounded deviated permutations
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2014
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Abstract
本篇論文的研究目的是要在均勻分佈的假設下,探索bounded deviated permutations的第一位置統計量的分佈情形,而我們猜測其將為常態分佈。
定義好與第一位置統計量相關的隨機變數後,藉由考慮雙變數生成函數,我們可以計算此隨機變數的平均數和變異數,本篇論文將把這個方法應用在三個特殊的情形上。因為這個雙變數生成函數的係數並沒有closed form,在計算過程中,我們會使用Hayman's formula求其漸進式。最後,使用電腦計算,這三個特殊的情形確實收斂到常態分佈,證實了我們的猜測。
The purpose of the thesis is to investigate the distribution of the leading statistic in the bounded deviated permutations S_{n+1}^{ℓ,r}, assuming the uniform distribution in S_{n+1}^{ℓ,r}. Define the random variable X_{n} to take the value k if π₁=k+1 for π=π₁π₂⋯π_{n+1}∈S_{n+1}^{ℓ,r}. By considering the bivariate generating function A(z,u), we could calculate the expected value and the standard deviation for X_{n}. The method is then applied to three specific cases, S_{n+1}^{1,2}, S_{n+1}^{1,3} and S_{n+1}^{2,2}. Since the coefficients λ_{n,k} of the bivariate generating function do not have a closed form, we will apply the Hayman method to get its asymptotic formula. Finally, by running computer programs, the convergence of the normal distribution on these three cases are verified.
The purpose of the thesis is to investigate the distribution of the leading statistic in the bounded deviated permutations S_{n+1}^{ℓ,r}, assuming the uniform distribution in S_{n+1}^{ℓ,r}. Define the random variable X_{n} to take the value k if π₁=k+1 for π=π₁π₂⋯π_{n+1}∈S_{n+1}^{ℓ,r}. By considering the bivariate generating function A(z,u), we could calculate the expected value and the standard deviation for X_{n}. The method is then applied to three specific cases, S_{n+1}^{1,2}, S_{n+1}^{1,3} and S_{n+1}^{2,2}. Since the coefficients λ_{n,k} of the bivariate generating function do not have a closed form, we will apply the Hayman method to get its asymptotic formula. Finally, by running computer programs, the convergence of the normal distribution on these three cases are verified.
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有界偏差排列, 第一位置統計量, 常態分佈, 雙變數生成函數, quasi-powers 定理, Hayman's 公式, bounded deviated permutation, leading statistic, normal distribution, bivariate generating function, quasi-powers theorem, Hayman’s method