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Characterizations of Normal Distribution 正态分布的特征
Pub Date : 2014-01-01 DOI: 10.2991/978-94-6239-061-4_8
M. Ahsanullah, B. M. Kibria, M. Shakil
Before a particular probability distribution model is applied to fit the real world data, it is necessary to confirm whether the given probability distribution satisfies the underlying requirements by its characterization.
在应用特定的概率分布模型来拟合现实世界的数据之前,有必要通过其表征来确认给定的概率分布是否满足底层要求。
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引用次数: 0
THE ESTIMATION OF DISTRIBUTIONS UNDER A PARTICULAR RANDOM CENSORING 在特定随机审查下的分布估计
Pub Date : 1993-01-01 DOI: 10.1515/9783112318867-049
W. Lu
Let X_1; X_2,…,X_N be i.i.d. random variables with distribution function F and censored by Y_1 Y_2…, Y_N. We can only observe (Z_t δ_t), i=1, 2,…, n and δ_i,i= n+1,…, N, where This model was proposed by Suzuki, K. (1985) and he discussed the case tnat X_t is a discrete random variable taking finite values. In this paper we discuss the case that X_t has a continuous distribution function F. We propose a estimator F of F and prove that N~(1/2)(F(t)-F(t)) converges to a Gussion process.
让X_1;X_2,…,X_N是iid个随机变量,其分布函数为F,并被Y_1, Y_2,…,Y_N截断。我们只能观察到(Z_t δ_t), i= 1,2,…,n和δ_i,i= n+1,…,n,其中这个模型是由Suzuki, k(1985)提出的,他讨论了X_t是一个离散随机变量取有限值的情况。本文讨论了X_t具有连续分布函数F的情况,给出了F的一个估计量F,并证明了N~(1/2)(F(t)-F(t))收敛于一个Gussion过程。
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引用次数: 0
REVERSIBILITY AND ENTROPY PRODUCTION OF MARKOV PROCESSES 马尔可夫过程的可逆性和熵的产生
Pub Date : 1985-01-01 DOI: 10.1090/conm/118/1137974
M. Qian
In the present paper,a general probabilistic definition of the entropy production for stochastic processes is given.In the concrete cases of Markov chains and diffussions,we get its explicit expressions,which meet those given by physists and chemists perfectly. Therefore,it could be seen that the entropy production is really a criterion to describe how far a stochastic process is from the reversibility.
本文给出了随机过程熵产生的一般概率定义。在马尔可夫链和扩散的具体情况下,我们得到了它的显式表达式,完全符合物理学家和化学家给出的表达式。由此可见,熵产实际上是描述随机过程离可逆性有多远的一个标准。
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引用次数: 21
期刊
应用概率统计
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