In this paper, we develop a new general class of skew distributions with flexibility properties on the tails. Moreover, such class can provide heavy and light tails. Some of its mathematical properties are studied, including the quantile function, the moments, the moment generating function and the mean of deviations. New skew distributions are derived and used to construct new models capturing asymmetry inherent to data. The estimation of the class parameters is investigated by the method of maximum likelihood and the performance of the estimators is assessed by a simulation study. Applications of the proposed distribution are explored for two climate data sets. The first data set concerns the annual heat wave index and the second data set involves temperature and precipitation measures from the meteorological station located at Schiphol, Netherlands. Data fitting results show that our models perform better than the competitors.

在本文中，我们开发了一种新的一般类偏斜分布，其尾部具有灵活性。此外，此类可以提供重尾和轻尾。研究了它的一些数学性质，包括分位数函数、矩、矩生成函数和偏差的平均值。新的偏斜分布被导出并用于构建捕捉数据固有的不对称性的新模型。通过最大似然法研究类参数的估计，并通过模拟研究评估估计器的性能。针对两个气候数据集探索了建议分布的应用。第一个数据集涉及年度热浪指数，第二个数据集涉及位于史基浦的气象站的温度和降水量，荷兰。数据拟合结果表明，我们的模型比竞争对手表现更好。