Data from some research fields tend to exhibit a positive skew. For example, in experimental psychology, reaction times (RTs) are characterised as being positively skewed. However, it is not unlikely that RTs can take a normal or, even, a negative shape. While the Ex-Gaussian distribution is suitable to model positively skewed data, it cannot cope with negatively skewed data. This manuscript proposes a distribution that can deal with both negative and positive skews: the exponential-centred skew-normal (ECSN) distribution. The mathematical properties of the proposed distribution are reported, and it is featured in two non-synthetic datasets.

中文翻译：

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以指数为中心的偏态正态分布

来自某些研究领域的数据倾向于呈现正偏差。例如，在实验心理学中，反应时间 (RT) 的特征是正偏斜。然而，RT 呈现正常甚至负值的情况并非不可能。虽然 Ex-Gaussian 分布适合对正偏态数据进行建模，但它不能处理负偏态数据。这份手稿提出了一种可以处理负偏斜和正偏斜的分布：指数中心偏斜正态 (ECSN) 分布。报告了提议分布的数学特性，它在两个非合成数据集中有特色。