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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/83249


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    題名: 常用統計套裝軟體的U(0,1)亂數產生器之探討
    作者: 張浩如
    Chang, Hao-Ju
    貢獻者: 余清祥
    張浩如
    Chang, Hao-Ju
    關鍵詞: 亂數產生器
    統計軟體
    樣本平均蒙地卡羅法
    Random number generator
    Statistical software
    sample-mean Monte Carlo method
    日期: 2000
    上傳時間: 2016-03-31 14:44:52 (UTC+8)
    摘要: 由於電腦的發展與普及，在各個領域的應用上，有越來越多的人利用電腦模擬的結果作為參考的依據。而在電腦模擬的過程中，亂數的產生是相當重要的一環。目前大多數的使用者都是直接利用套裝軟體內設的亂數產生器（random number generator）來產生亂數，但是在一般的文獻中對於各軟體內設的亂數產生器，則少有詳盡的探討。因此本論文的主要目的在於：針對SAS 6.12、SPSS 8.0、EXCEL 97、S-PLUS 2000及MINITAB 12等五種統計分析上常使用的套裝軟體，針對其內設U(0,1)亂數產生器進行較完整的介紹、比較、與探討。除了從週期長短、統計性質、電腦執行效率等三種不同觀點來評估這五種軟體內設亂數產生器的優劣之外，同時亦利用樣本平均蒙地卡羅法（sample-mean Monte Carlo method）在求解積分值上的表現作為電腦模擬的應用實例。
    With the development and popularity of computers, in different fields more and more people are using the result from computer simulation as reference. The generation of random number is one of the most important factors in applying computer simulation. Nowadays most of users use intrinsic random number generators in software to produce random numbers. However, only a few articles focus on detailed comparisons of those random number generators. Thus, in this study, we explore the random number generators in frequently used statistical software; such as SAS 6.12, SPSS 8.0, EXCEL 97, S-PLUS 2000, MINITAB 12, etc. and discuss their performances in uniform (0,1) random number generators. This study focuses not only on the comparison of period length and statistical properties of these random number generators, but also on computer executive efficiency. In addition, we also use sample-mean Monte Carlo method as an integral example of computer simulation to evaluate these random number generators.
    參考文獻: I. 中文書目
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    II. 英文書目
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    19. Marsaglia, G. (1985), “Matrices and the structure of random number sequences,” Linear algebraic and its appl., 67,147-156.
    20. Marsaglia, G., Zaman, A., and Tsand, W.W. (1990), “Toward a universal random number generator,” Statistics & Proability Letters, 8, 35-39.
    21. Matteis, A.D., and Pagnutti, S. (1988), “Parallelization of random number generators and long-range correlation,” Numer. Math., 53,595-608.
    22. Montgomery, D.C. (1997), Design and analysis of experiments, Wiley, New York.
    23. Moore, D. S. (1986), Tests of chi-squared type. In Goodness-of-Fit Techniques. New York: Marcel Dekker.
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    25. Ripley, B.D. (1987), Stochastic Simulation, Wiley, New York.
    26. Ripley, B.D. (1999), Modern applied statistics with S-PLUS, Springer-Verlag, New York, 3rd.
    27. Rubinstein, R.Y. (1981), Simulation and the Monte Carlo Method, John Wiley, New York.
    28. Tausworthe, R.C. (1965), “Random numbers generated by linear recurrence modulo two,” Math. Camp.19, 201-209.
    29. Wichmann, B. A., and Hill, J. D. (1982), “Algorithm AS183. An efficient and portable pseudo-random number generator,” Appl Statist. 31, 188-190; 33, 123.
    30. Ziesel, H. (1986), “A remark on AS 183. An efficient and portable pseudo-random number generator,” Appl Statist. 35, 89.
    描述: 碩士
    國立政治大學
    統計學系
    87354012
    資料來源: http://thesis.lib.nccu.edu.tw/record/#A2002001943
    資料類型: thesis
    顯示於類別:[統計學系] 學位論文

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