A new method for including systematic errors in the regression with Poisson data is reviewed in this contribution, with emphasis on applications to astronomical spectra. The method consists of generalizing the usual Poisson log-likelihood, known as the Cash statistic $C_{min}$, and its associated likelihood-ratio statistic $ΔC$, to include the presence of systematic sources of uncertainty. Advantages of this new method include its modeling simplicity and its ability to assess both the level of systematics and the goodness of fit at the same time, including for a nested model component.

翻译：本文综述了一种在泊松数据回归中包含系统误差的新方法，重点讨论了其在天文光谱中的应用。该方法将通常的泊松对数似然函数（即Cash统计量$C_{min}$）及其相关的似然比统计量$ΔC$进行推广，以纳入不确定性中的系统来源。该新方法的优势包括建模简便，以及能够同时评估系统误差水平和拟合优度（包括嵌套模型分量）。