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A DENSITY FUNCTION CONNECTED WITH A NON-NEGATIVE SELF-DECOMPOSABLE RANDOM VARIABLE

机译:与非负自分解随机变量有关的密度函数

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The innovation random variable for a non-negative self-decomposable random variable can have a compound Poisson distribution. In this case, we provide the density function for the compounded variable. When it does not have a compound Poisson representation, there is a straightforward and easily available compound Poisson approximation for which the density function of the compounded variable is also available. These results can be used in the simulation of Ornstein-Uhlenbeck type processes with given marginal distributions. Previously, simulation of such processes used the inverse of the corresponding tail Levy measure. We show this approach corresponds to the use of an inverse cdf method of a certain distribution. With knowledge of this distribution and hence density function, the sampling procedure is open to direct sampling methods.
机译:非负自分解随机变量的创新随机变量可以具有复合泊松分布。在这种情况下,我们为复合变量提供了密度函数。当它不具有复合泊松表示时,有一个简单易用的复合泊松近似,其复合变量的密度函数也可用。这些结果可用于模拟具有给定边际分布的Ornstein-Uhlenbeck型过程。以前,此类过程的模拟使用相应的尾部Levy度量的反函数。我们显示此方法对应于使用具有一定分布的逆cdf方法。了解了这种分布并因此了解了密度函数,就可以采用直接采样方法进行采样。

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