在本篇論文中，我們將探討 Kennedy 在 1988 年所提出的一隨機搜尋過程，可用來生成近似的 beta 變量。我們的目標是確認最佳的參數設定，使得 Kennedy 的演算法可以達到最快的生成速度。為了評估所提演算法之效能，我們也探討一些文獻中常用的 beta 演算法，並以下列準則來作比較：(i) 形狀參數的適用區域；(ii) 計算時間；(iii) 適合度；以及 (iv) 演算法所需的隨機變數。最後透過這些比較，我們提供兩個方針來選擇最適合的生成 beta 變量之方法。 In this paper, we study a stochastic search procedure proposed by Kennedy (1988) that asymptotically generates a beta variate. The goal is to identify the optimal parameter setting so that Kennedy's algorithm can achieve the fastest speed of generation. For comparative purposes, we also review some well-known beta algorithms and evaluate their performance in terms of the following criteria: (i) validity of choice of shape parameters, (ii) computer time, (iii) goodness-of-fit, and (iv) amount of random number generation required. Based on the empirical study, we present two guidelines for choosing the best suited beta algorithm.
