ABSTRACT In the big data era, it is often needed to resolve the problem of parsimonious data representation. In this paper, the data under study are curves and the sparse representation is based on a semiparametric model. Indeed, we propose an original registration model for noisy curves. The model is built transforming an unknown function by plane similarities. We develop a statistical method that allows to estimate the parameters characterizing the plane similarities. The properties of the statistical procedure are studied. We show the convergence and the asymptotic normality of the estimators. Numerical simulations and a real-life aeronautic example illustrate and demonstrate the strength of our methodology.

中文翻译：

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平面相似度的半参数估计：应用于航空载荷的快速计算

摘要 在大数据时代，往往需要解决简约的数据表示问题。在本文中，所研究的数据是曲线，稀疏表示基于半参数模型。事实上，我们为嘈杂的曲线提出了一个原始的配准模型。该模型是通过平面相似性转换未知函数而构建的。我们开发了一种统计方法，可以估计表征平面相似性的参数。研究了统计过程的特性。我们展示了估计量的收敛性和渐近正态性。数值模拟和真实的航空示例说明并证明了我们方法的优势。