This note reconsiders the marginal density of a threshold moving average process and proposes a simple yet effective numerical algorithm to implement that by solving an associated integral equation. This algorithm can also be applied to calculate stationary probability density or distribution functions of a few other types of nonlinear stationary stochastic processes numerically.

中文翻译：

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TMA(1) 过程的边际密度

本笔记重新考虑了阈值移动平均过程的边际密度，并提出了一种简单而有效的数值算法，通过求解相关的积分方程来实现该算法。该算法还可用于数值计算其他几种非线性平稳随机过程的平稳概率密度或分布函数。