Mathematical Sciences: Multilinear Analysis of SpectroscopicData

这是一个统计学家和 生物物理化学家将完善和扩展分析， 光谱数据 光谱学是测量 从样品中吸收或发射粒子。 的 蛋白质的荧光光谱对许多 不同的元素，而且经常严重重叠。 的 光谱数据的新特征是其高信号- 噪声比 新的统计技术将利用 数据的特殊特征，并针对具体的 感兴趣的问题 在标准因子分析中， 假设响应变量的期望是线性的， 未知参数的函数 光谱的性质 数据使得有必要使用非线性函数的 参数

This collaborative project between a statistician and a biophysical chemist will refine and extend analyses of spectroscopic data. Spectroscopy is the measurement of the absorption or emission of particles from a specimen. The fluorescence spectra of proteins are highly sensitive to many different elements, and are frequently severely overlapping. The novel feature of the spectroscopic data is its high signal-to- noise ratio. The new statistical techniques will make use of the special features of the data and address the analysis to specific questions of interest. In standard factor analysis, the expectation of the response variable is assumed to be a linear function of unknown parameters. The nature of the spectroscopic data make it necessary to use non-linear functions of the parameters.