ABSTRACT

We present PLSIM, a new method for generating nonnormal data with a pre-specified covariance matrix that is based on coordinate-wise piecewise linear transformations of standard normal variables. In our presentation, the piecewise linear transforms are chosen to match pre-specified skewness and kurtosis values for each marginal distribution. We demonstrate the flexibility of the new method, and an implementation using R software is provided.

中文翻译：

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使用分段线性变换的非正态数据模拟

摘要

我们提出了 PLSIM，这是一种使用预先指定的协方差矩阵生成非正态数据的新方法，该矩阵基于标准正态变量的坐标分段线性变换。在我们的演示中，选择分段线性变换以匹配每个边缘分布的预先指定的偏度和峰度值。我们展示了新方法的灵活性，并提供了使用 R 软件的实现。