具有概率约束的委托代理模型

具有概率约束的委托代理模型于维生金成晓ＡＢＳＴＲＡＣＴＰａｒｔｉｃｉｐａｔｉｏｎｃｏｎｓｔｒａｉｎｔｓｉｎａｇｅｎｔｅｎｔｒｕｓｔｍｏｄｅｌｗｅｒｅｍｏｄｉｆｉｅｄｂｙｐｒｏｂａｂｉｌｉｔｙｃｏｎｓｔｒａｉｎｔｓ,ｓｏｔｈａｔｔｈｅｅｘｐｒｅｓｓｉｏ...     

论整群不等概率抽样技术

论整群不等概率抽样技术彭念一ＡＢＳＴＲＡＣＴＴｈｅｐａｐｅｒｄｉｓｃｕｓｓｅｄｔｈｅｉｍｐｏｒｔａｎｔｓｉｇｎｉｆｉｃａｎｃｅｏｆｓａｍｐｌｉｎｇｔｅｃｈｎｏｌｏｇｙｗｉｔｈｕｎｅｑｕａｌｐｒｏｂａｂｉｌｉｔｙ,ｅｘｐｏｕｎｄｅｄｉｔｓｂａｓｉｃｐｒ...     

Use of the Correlation Coefficient with Normal Probability Plots

The use of the correlation coefficient is suggested as a technique for summarizing and objectively evaluating the information contained in probability plots. Goodness-of-fit tests are constructed using this technique for several commonly used plotting positions for the normal distribution. Empirical sampling methods are used to construct the null distribution for these tests, which are then compared on the basis of power against certain nonnormal alternatives. Commonly used regression tests of fit are also included in the comparisons. The results indicate that use of the plotting position p_i = (i - .375)/(n + .25) yields a competitive regression test of fit for normality.     

挑战机率

近几年,各种彩票热遍江南塞北,充斥城市乡村。面对劝辄几十万、几百万的奖金数额,有人趋之若鹜、不惜血本,有人不屑一顾、一毛不 拔,也有人偶尔为之、小试身手。所谓人各有所好,不管以哪种方式参与,也不管热衷程度如何,都无可厚非,市场就是靠他们在搭台、在唱 戏。我们要告诉您的是,无论哪种游戏,都有着它的一定规则,彩票市 场恐怕也不例外。而分折彩票市场的规则,进而选择自己的投资取向,机率统计完全可以派上大用场。能以随机的方式来思考问题,这是彩票带 给统计的收获。 我们在此刊登黄文璋教授《挑战机率》一文,目的,不是教您怎么买彩票,而是想把统计在这领域的作用介绍给您。进一步地告诉您,统 计的应用就是这么的货真价实。     

Probability inequalities for continuous unimodal random variables with finite support

A paramecer-free Bernstein-type upper bound is derived for the probability that the sum S of n i.i.d, unimodal random variables with finite support, X₁ ,X₂,…,X_n, exceeds its mean E(S) by the positive value nt. The bound for P{S - nμ ≥ nt} depends on the range of the summands, the sample size n, the positive number t, and the type of unimodality assumed for X_i. A two-sided Gauss-type probability inequality for sums of strongly unimodal random variables is also given. The new bounds are contrasted to Hoeffding's inequality for bounded random variables and to the Bienayme-Chebyshev inequality. Finally, the new inequalities are applied to a classic probability inequality example first published by Savage (1961).