We consider the statistical problem of estimating constituent curves from observations of their aggregated curves, referred to as aggregated functional data, in models with additive errors. A typical model arises in chemometrics via the Beer-Lambert law. The package FunctionalCalibration provides functions to estimate individual curves from aggregated curves by using splines or wavelet basis expansion.

翻译：我们考虑在具有加性误差的模型中，从聚合曲线（即聚合函数数据）的观测中估计组成曲线的统计问题。一个典型模型源于化学计量学中的比尔-朗伯定律。FunctionalCalibration软件包提供通过样条或小波基展开从聚合曲线估计个体曲线的函数。